{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3a44d14d-d9ff-4a32-b478-d3d6f4cde48a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-06T09:05:26.808021Z",
     "iopub.status.busy": "2023-11-06T09:05:26.806913Z",
     "iopub.status.idle": "2023-11-06T09:05:29.733062Z",
     "shell.execute_reply": "2023-11-06T09:05:29.731905Z",
     "shell.execute_reply.started": "2023-11-06T09:05:26.807985Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using backend: paddle\r\n",
      "Other available backends: tensorflow.compat.v1, tensorflow, pytorch, jax.\r\n",
      "paddle supports more examples now and is recommended.\r\n",
      " \r\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib  \n",
    "from matplotlib import pyplot as plt\n",
    "import deepxde as dde\n",
    "import os\n",
    "\n",
    "main_path = os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "15528d0e-3f70-4791-9203-1a2389617f63",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-06T09:05:32.346662Z",
     "iopub.status.busy": "2023-11-06T09:05:32.345960Z",
     "iopub.status.idle": "2023-11-06T09:05:33.276547Z",
     "shell.execute_reply": "2023-11-06T09:05:33.274798Z",
     "shell.execute_reply.started": "2023-11-06T09:05:32.346627Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Set the default float type to float32\r\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1920x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: CSGDifference.uniform_points not implemented. Use random_points instead.\r\n",
      "[4522, 4522, 4522, 4522]\r\n",
      "4522\r\n"
     ]
    }
   ],
   "source": [
    "# 需要对哪个level的网格进行加密？\n",
    "level = 1\n",
    "\n",
    "\"\"\"------------------------------ Fluid parameters  -----------------------\"\"\"\n",
    "# The universal gas constant 气体常数 (FOR AIR HERE)\n",
    "R = 286.9 #(J/Kg.K)\n",
    "\n",
    "# 空气绝热指数\n",
    "k = 1.4\n",
    "\n",
    "# 用于无量纲化的速度、压力和密度，取入口处的声速值、压力值和密度值\n",
    "p0 = 73048 #(pa)\n",
    "rho0 = 0.9 #(kg/m^3)\n",
    "a0 = np.sqrt(k*p0/rho0) #(m/s)\n",
    "\n",
    "\"\"\"------------------------------ NACA633418 shape -----------------------\"\"\"\n",
    "airfoil_boundary_points = np.load(\"../0_Mesh_files/ordered_airfoil_points.npy\")[:, 0:2]\n",
    "airfoil = dde.geometry.Polygon(airfoil_boundary_points)\n",
    "\n",
    "\"\"\"------------------------------------ Training Spatio-temporal region --------------------------------------\"\"\"\n",
    "\"\"\"-------------- Rectangular -------------\"\"\"\n",
    "x_min, x_max = -5.5, 6.5\n",
    "L = x_max - x_min\n",
    "\n",
    "y_min, y_max = -2.0, 2.0\n",
    "H = y_max - y_min\n",
    "\n",
    "\"\"\"Spatial region definition\"\"\"\n",
    "farfield = dde.geometry.Rectangle([x_min, y_min], [x_max, y_max])  # 设置左下角和右上角坐标\n",
    "geom = dde.geometry.CSGDifference(farfield, airfoil)\n",
    "\n",
    "\"\"\"------------------------------ Navier Stokes Equation(Time-dependent PDE) -----------------------\"\"\"\n",
    "def DL_Euler_Equation_2D(x, y):\n",
    "    \"\"\"\n",
    "    System of PDEs to be minimized: compressible 2D Euler equations.\n",
    "\n",
    "    \"\"\"\n",
    "    gamma = 1.4\n",
    "    \n",
    "    u = y[:, 0:1]\n",
    "    v = y[:, 1:2]\n",
    "    p = y[:, 2:3]\n",
    "    rho = y[:, 3:4]\n",
    "\n",
    "    E = p/(gamma-1) + 0.5*rho*(u*u + v*v)\n",
    "\n",
    "    A1, B1 = rho*u, rho*v\n",
    "    A2, B2 = gamma*rho*u*u + p, gamma*rho*u*v\n",
    "    A3, B3 = gamma*rho*u*v, gamma*rho*v*v + p\n",
    "    A4, B4 = u*E, v*E\n",
    "\n",
    "    dA1_x = dde.grad.jacobian(A1, x, i=0, j=0)\n",
    "    dB1_y = dde.grad.jacobian(B1, x, i=0, j=1)\n",
    "\n",
    "    dA2_x = dde.grad.jacobian(A2, x, i=0, j=0)\n",
    "    dB2_y = dde.grad.jacobian(B2, x, i=0, j=1)\n",
    "\n",
    "    dA3_x = dde.grad.jacobian(A3, x, i=0, j=0)\n",
    "    dB3_y = dde.grad.jacobian(B3, x, i=0, j=1)\n",
    "\n",
    "    dA4_x = dde.grad.jacobian(A4, x, i=0, j=0)\n",
    "    dB4_y = dde.grad.jacobian(B4, x, i=0, j=1)\n",
    "    \n",
    "    continuity = dA1_x + dB1_y\n",
    "    x_momentum = dA2_x + dB2_y\n",
    "    y_momentum = dA3_x + dB3_y\n",
    "    energy = dA4_x + dB4_y\n",
    "    return [continuity, x_momentum, y_momentum, energy]\n",
    "\n",
    "\"\"\"---------------------------------------- Boundary Definition -------------------------------------------\"\"\"\n",
    "\"\"\"Boundary definition of rectangle domain\"\"\"\n",
    "def boundary_inlet(x, on_boundary):\n",
    "    \"\"\"Checks the inlet boundary\"\"\"\n",
    "    return np.isclose(x[0], x_min)\n",
    "\n",
    "def boundary_outlet(x, on_boundary):\n",
    "    \"\"\"Checks the outlet boundary\"\"\"\n",
    "    return np.isclose(x[0], x_max)\n",
    "\n",
    "def boundary_top_bottom(x, on_boundary):\n",
    "    \"\"\"Checks the bottom boundary\"\"\"\n",
    "    return (np.isclose(x[1], y_min) or np.isclose(x[1], y_max))\n",
    "\n",
    "\"\"\"Boundary definition of cylinder domain\"\"\"\n",
    "def boundary_airfoil(x, on_boundary):\n",
    "    return on_boundary and (not farfield.on_boundary(x))\n",
    "\n",
    "'''-----------------------Defining BC for u, v, and p (component = 0, 1, 2 resp assign)---------------------------\n",
    "------------------------------\n",
    "Dirichlet boundary conditions:\n",
    "    y(x) = func(x)\n",
    "------------------------------\n",
    "Neumann boundary conditions: \n",
    "    dy/dn(x) = func(x)\n",
    "------------------------------'''\n",
    "# Boundary values definition\n",
    "def No_slip(x): # 无滑移\n",
    "    return 0.0\n",
    "\n",
    "def uniform_flow(x): # 无滑移\n",
    "    return 0.7\n",
    "\n",
    "def Zero_v(x):  # 零速度\n",
    "    return 0.0\n",
    "\n",
    "def Zero_p(x):  # 零压力\n",
    "    return 0.0\n",
    "\n",
    "'''----------------------- Other functions ---------------------------'''\n",
    "def gen_training_points():\n",
    "    mesh_xy_points = data_points[:, 0:2]\n",
    "    return mesh_xy_points\n",
    "\n",
    "def plot_points_xy(points, color=\"k\", marker=\".\"):\n",
    "    figure = plt.figure(dpi=300)\n",
    "    axis = figure.add_subplot(111)\n",
    "    axis.scatter(points[:, 0], points[:, 1], s=0.5, color=color, marker=marker)\n",
    "    plt.axis(\"scaled\")  # 设置x轴和y轴相同的缩放比例\n",
    "    plt.savefig('./Figs/Total_points.png', dpi=300)\n",
    "    plt.show()\n",
    "    \n",
    "\n",
    "def plot_flow_field():\n",
    "    import matplotlib as mpl\n",
    "    from matplotlib import rcParams\n",
    "    config = {\"font.size\": 16}\n",
    "    rcParams.update(config)\n",
    "    plt.rcParams['xtick.direction'] = 'in'\n",
    "    plt.rcParams['ytick.direction'] = 'in'\n",
    "    '''------------------------------------------- Model validation ---------------------------------------------'''\n",
    "    '''------------------Plotting 2------------------'''\n",
    "\n",
    "    test_data = data_xy\n",
    "\n",
    "    # Model predictions generation\n",
    "    u = model.predict(test_data)[:, 0] * a0\n",
    "    v = model.predict(test_data)[:, 1] * a0\n",
    "    p = model.predict(test_data)[:, 2] * p0\n",
    "    rho = model.predict(test_data)[:, 3] * rho0\n",
    "\n",
    "    airfoil_plot = airfoil_boundary_points[:, 0:2]\n",
    "\n",
    "    # plot\n",
    "    fig, ax = plt.subplots(figsize=(10, 4))\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], (u**2 + v**2)**0.5, levels=1000, cmap=\"coolwarm\", vmin=36.5, vmax=467)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=36.5, vmax=467)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[m/s]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Velocity Magnitude')\n",
    "    plt.savefig(\"./Figs/Velocity.png\", dpi=300)\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(10, 4))\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], p, levels=1000, cmap=\"coolwarm\", vmin=19900, vmax=100000)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=19900, vmax=100000)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[Pa]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Pressure')\n",
    "    plt.savefig(\"./Figs/P.png\", dpi=300)\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(10, 4))\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], rho, levels=1000, cmap=\"coolwarm\", vmin=0.341, vmax=1.13)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=0.341, vmax=1.13)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[kg/m^3]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Density')\n",
    "    plt.savefig(\"./Figs/Rho.png\", dpi=300)\n",
    "    plt.show()\n",
    "    \n",
    "     \n",
    "\n",
    "def make_dir():\n",
    "    # 保存训练结果需要的文件\n",
    "    # 模型保存地址\n",
    "    Model_path = \"Model/\"  \n",
    "    # 图片保存地址\n",
    "    Figs_path = \"Figs/\"  \n",
    "    # Loss保存地址\n",
    "    Train_history_path = \"Train_history/\"  \n",
    "\n",
    "    if not os.path.exists(Model_path):\n",
    "    \tos.mkdir(Model_path)\n",
    "    if not os.path.exists(Figs_path):\n",
    "    \tos.mkdir(Figs_path)\n",
    "    if not os.path.exists(Train_history_path):\n",
    "    \tos.mkdir(Train_history_path)\n",
    "\n",
    "def plot_loss_history(loss_history, fname=None):\n",
    "    loss_train = np.sum(loss_history.loss_train, axis=1)\n",
    "    loss_test = np.sum(loss_history.loss_test, axis=1)\n",
    "\n",
    "    plt.figure()\n",
    "    plt.semilogy(loss_history.steps, loss_train, label=\"Train loss\")\n",
    "    for i in range(len(loss_history.metrics_test[0])):\n",
    "        plt.semilogy(\n",
    "            loss_history.steps,\n",
    "            np.array(loss_history.metrics_test)[:, i],\n",
    "            label=\"Test metric\",\n",
    "        )\n",
    "    plt.xlabel(\"# Steps\")\n",
    "    plt.legend()\n",
    "\n",
    "    if isinstance(fname, str):\n",
    "        plt.savefig(fname, dpi=300)\n",
    "\n",
    "\n",
    "\n",
    "'''-------------------------------------------------------------- training model:  ------------------------------------------------------------------'''\n",
    "dde.config.set_random_seed(1234)\n",
    "dde.config.set_default_float(\"float32\")\n",
    "\n",
    "make_dir()\n",
    "\n",
    "'''------------------BC------------------'''\n",
    "# data\n",
    "data_points = np.load('../1_Fluent_results/level' + str(level) + '_fluent_results.npy')\n",
    "\n",
    "# 此处注意无量纲化\n",
    "data_xy = data_points[:, 0:2]\n",
    "data_u = data_points[:, 2:3]/a0\n",
    "data_v = data_points[:, 3:4]/a0\n",
    "data_p = data_points[:, 4:5]/p0\n",
    "data_rho = data_points[:, 5:6]/rho0\n",
    "\n",
    "data_u = dde.icbc.PointSetBC(data_xy, data_u, component = 0)\n",
    "data_v = dde.icbc.PointSetBC(data_xy, data_v, component = 1)\n",
    "data_p = dde.icbc.PointSetBC(data_xy, data_p, component = 2)\n",
    "data_rho = dde.icbc.PointSetBC(data_xy, data_rho, component = 3)\n",
    "\n",
    "bcs = [\n",
    "      data_u,\n",
    "      data_v,\n",
    "      data_p,\n",
    "      data_rho,\n",
    "]\n",
    "'''--------------- Training Model ----------------'''\n",
    "# 根据目前的geomtime生成训练点\n",
    "total_points = gen_training_points()\n",
    "plot_points_xy(total_points)\n",
    "\n",
    "'''----Training datasets and Loss function ----'''\n",
    "data = dde.data.PDE(geom,\n",
    "              DL_Euler_Equation_2D, # Loss function\n",
    "              bcs,                 # IC and BC\n",
    "              num_domain = 0,      # training data\n",
    "              num_boundary = 0,     # boundary data\n",
    "              num_test = 1000,         # test data\n",
    "              anchors = total_points,\n",
    "              )         \n",
    "print(data.num_bcs)\n",
    "print(data.train_x_all.shape[0])\n",
    "\n",
    "'''--------- Neural Network setup ---------'''\n",
    "layer_size = [2] + [40] * 6 + [4]\n",
    "activation = \"tanh\"\n",
    "initializer = \"Glorot uniform\"\n",
    "net = dde.nn.FNN(layer_size, activation, initializer)\n",
    "\n",
    "'''-------- Compile, Training and save Model --------'''\n",
    "model = dde.Model(data, net)\n",
    "weights = [1] * 4 + [10] * 4\n",
    "\n",
    "# first use Adam to find a roughly good solution, \n",
    "# model.compile(\"adam\", lr=1e-3, loss_weights = weights)\n",
    "# loss_history, train_state = model.train(epochs=20000, display_every=100)\n",
    "# plot_loss_history(loss_history, \"./Train_history/Loss.png\")\n",
    "# dde.saveplot(loss_history, train_state, issave=True, isplot=True, output_dir = \"./Train_history\")\n",
    "# model.save(save_path=\"./Model/model\")\n",
    "# # plot_flow_field()\n",
    "\n",
    "# model.compile(\"adam\", lr=5e-4, loss_weights = weights)\n",
    "# loss_history, train_state = model.train(epochs=20000, display_every=100)\n",
    "# plot_loss_history(loss_history, \"./Train_history/Loss.png\")\n",
    "# dde.saveplot(loss_history, train_state, issave=True, isplot=True, output_dir = \"./Train_history\")\n",
    "# model.save(save_path=\"./Model/model\")\n",
    "# # plot_flow_field()\n",
    "\n",
    "# model.compile(\"adam\", lr=1e-4, loss_weights = weights)\n",
    "# loss_history, train_state = model.train(epochs=20000, display_every=100)\n",
    "# plot_loss_history(loss_history, \"./Train_history/Loss.png\")\n",
    "# dde.saveplot(loss_history, train_state, issave=True, isplot=True, output_dir = \"./Train_history\")\n",
    "# model.save(save_path=\"./Model/model\")\n",
    "# plot_flow_field()\n",
    "\n",
    "# # and then use L-BFGS to search a local minimum.\n",
    "# model.compile(optimizer=\"L-BFGS\", loss_weights = weights)\n",
    "# # Optional: Save the model during training.\n",
    "# checkpointer = dde.callbacks.ModelCheckpoint(\"Model/model\", verbose=1000, save_better_only=True)\n",
    "# loss_history, train_state = model.train(display_every=100, callbacks=[checkpointer])\n",
    "# plot_loss_history(loss_history, \"./Train_history/Loss.png\")\n",
    "# dde.saveplot(loss_history, train_state, issave=True, isplot=True, output_dir = \"./Train_history\")\n",
    "# model.save(save_path=\"./Model/model\")\n",
    "# plot_flow_field()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0c335565-6c07-4b7e-8b7e-c8a296bf1cc5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-06T09:05:43.174276Z",
     "iopub.status.busy": "2023-11-06T09:05:43.173684Z",
     "iopub.status.idle": "2023-11-06T09:05:51.194355Z",
     "shell.execute_reply": "2023-11-06T09:05:51.193129Z",
     "shell.execute_reply.started": "2023-11-06T09:05:43.174239Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling model...\r\n",
      "'compile' took 0.000718 s\r\n",
      "\r\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA20AAAFbCAYAAABGTmZTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAACWvklEQVR4nO2deXgUVbr/v1WdPYQARtawqQMMwXFkUHCAUQnqACIqgssohovichUVVEDF5YIyjCviBoriMg4gi4IoPwheGUBEuTBi2AIKAgKyRJOQhCxd9fujuzpV3dVL9VpV/f08Tz+QrjpVp6u38+n3Pe8RZFmWQQghhBBCCCHElIiJ7gAhhBBCCCGEEP9Q2gghhBBCCCHExFDaCCGEEEIIIcTEUNoIIYQQQgghxMRQ2gghhBBCCCHExFDaCCGEEEIIIcTEUNoIIYQQQgghxMRQ2gghhBBCCCHExFDaCCGEEEIIIcTEUNoIIYQQQgixCbt378asWbNQVFSEc889FykpKRAEAdOmTQvatri4GIMHD0ZeXh4yMzPRrVs3PProozh16lTAdnv37kVRURHy8/ORnp6O/Px8FBUV4ccffwzYrrKyEo888gi6du2KzMxM5OXlYciQIfjiiy8CtpMkCbNnz0bv3r2Rk5ODnJwc9O7dG3PmzIEsyzF5jIlGkIM9MkIIIYQQQogluP/++zFz5kyf+6dOnYrHHnvMb7sXX3wR48ePhyAI6N+/P1q1aoV169bh6NGj6Nq1K9avX4+8vDyfdhs2bMDll1+O6upqFBQUoEePHigpKcH27duRnZ2N4uJi9OnTx6fdsWPH0L9/f5SWlqJNmzbo168ffvnlF6xbtw4AMHPmTNx7770+7ZxOJ0aOHIklS5YgKysLhYWFAFwyVlNTgxEjRmD+/PkQRd/YVLiP0RTIhBBCCCGEEFvw5ptvyg8++KD8z3/+U965c6d8yy23yADkqVOn+m2zZcsWWRAE2eFwyJ999pnn/qqqKrmwsFAGIA8fPtynXVVVldy2bVsZgDx58mTNtsmTJ8sA5Pbt28vV1dU+bYcNGyYDkAsLC+WqqirP/StWrJAdDocsiqL83Xff+bR78cUXZQByu3bt5B9//NFz/48//ujpy6xZs6L2GM0CpY0QQgghhBCbcuuttwaVthEjRsgA5Ntuu81n2/79+2VRFGUA8s6dOzXbXn31VRmA3KVLF9npdGq2OZ1OuUuXLjIA+Y033tBs2759uwxAdjgc8v79+33OOWbMGBmAfMMNN/gcs3Xr1jIA+YMPPvBp9/7778sA5LZt2/r0J9zHaBY4p40QQgghhJAkpa6uDitWrAAA3HTTTT7bO3bsiL59+wIAli5dqtmm/H3DDTf4pCOKoojrr78eALBkyRLddn379kXHjh19zqn0Y/ny5aivr/fcv3HjRhw9ehTp6ekYPny4T7vhw4cjLS0Nhw8fxqZNm6LyGM0CpY0QQgghhJAkpbS0FNXV1QCAXr166e6j3L9161bN/crfsWpXVVWFPXv2+LQrKChARkaGT7vMzEwUFBT4nDOSx2gWUhLdAUIIIYQQQuzM6dOnUVdXF1ZbWZYhCILmvvT0dKSnp0eja9i3bx8AoFmzZsjJydHdp3379pp9AVflx5MnTwIAOnToELDd8ePHUVVVhezsbM1x/LVr2rQpmjZtioqKCuzbtw/du3cPqZ1yzq1bt2r6Gu5jNBOUNkIIIYQQQmLE6dOn0TazCX6FM6z2TZo08SlH/8QTT+DJJ5+MQu9c8gXAI1T++gAAFRUVPu0CtVXaKW2V/UI9Z0VFhe45w+2r0XZmgtJGCCGEEEJIjKirq8OvcGKeozOyDM5MqoaEolP7cPDgQTRt2tRzf7SibMQ6UNoIIYQQQgiJMdmpDmQJDkNtBNkJOBvTBWOBki5YVVXldx8l0qfugzrN0F9bdYRQr22454xXOzPBQiSEEEIIIYTEGCFFgGjwJqQIwQ8cIZ06dQIA/Pbbb5qURzUHDx7U7Au4RKhFixYAgAMHDgRsl5eXp0lNVI7jr506LVJ9zmDt/PU13MdoJihthBBCCCGExBghVQzrFmu6du2KrKwsAMDmzZt191Hu79mzp+Z+5e9YtcvOzkaXLl182m3fvh2nT5/2aVdTU4Pt27f7nDOSx2gWKG2EEEIIIYTEGNFhPNImOmIfaUtLS8OQIUMAAB9++KHP9p9++glfffUVAOCaa67RbFP+nj9/PiRJ0myTJAkLFiwAAFx77bWabVdffTUAYMOGDbpRM6UfQ4cORWpqquf+iy66CK1bt0ZtbS0WL17s027x4sWoq6tD27Zt0bt376g8RrNAaSOEEEIIISTGCKlCWLd4MGnSJAiCgHfeeQcrV6703F9dXY0xY8bA6XRi+PDh6Natm6ZdUVER2rZti9LSUkyZMkWzbcqUKSgtLUV+fj5GjRql2VZQUIBhw4bB6XRizJgxqKmp8Wz7/PPPMW/ePIiiiMmTJ2vaiaKIiRMnAgAmTpzoU9Z/0qRJAIDJkyf7LPYd7mM0C4Isy3KiO0EIIYQQQogdqaioQG5uLj5u83tki8YKkVRJTlx9ZCfKy8tDLpCxZcsW3H333Z6/f/jhB5w4cQL5+flo166d5/6lS5eiTZs2nr9ffPFFjB8/HoIg4OKLL0bLli2xbt06HDlyBF27dsX69euRl5fnc74NGzbg8ssvR3V1NXr06IEePXqgpKQEJSUlyM7ORnFxMfr06ePT7tixY+jXrx/27NmDNm3aoH///jh27BjWrl0LWZYxc+ZMjBs3zqed0+nEiBEjsHTpUmRlZWHgwIEAgOLiYlRXV+O6667DggULfKQtksdoBihthBBCCCGExAhF2pa17x6WtF11cIchafvyyy9x6aWXBt1v3759PkU3iouL8fzzz+Obb75BVVUVOnTogOuuuw6TJ0/2uyg1AOzduxdTp05FcXExjh8/jjPPPBMDBw7E448/jrPPPttvu4qKCkyfPh2LFy/GgQMHkJ2djQsvvBAPPvggCgsL/baTJAlvvvkm3nrrLezcuRMA0L17d4wZMwZjx471WYw8Go8x0VDaCCGEEEIIiRGKtC0/qyAsaRv643ZD0kbsCddpI4QQQgghJMaIDuOFRURnfOa0EfNDaSOEEEIIISTGCA4BgkFpE0BpIy4obYQQQgghhMSYsCJtlDbihiX/CSGEEEIIIcTEMNJGCCGEEEJIjBFEAYJoMD1SZqSNuKC0EUIIIYQQEmMEhwjBYSzJTQCLvBMXlDZCCCGEEEJiDOe0kUigtBFCCCGEEBJjBCGM9EiJ0kZcUNoIIYQQQgiJMYIDhiNtArMjiRtWjySEEEIIIYQQE8NIGyGEEEIIITEmrMW1WT2SuKG0EUIIIYQQEmMEUYQgGqweaXB/Yl8obYQQQgghhMSYsNZpM7g/sS/Ud0IICcC8efNcFb+8bqIoolmzZujZsyfGjx+PvXv3JrqrhBBCTIxS8t/ojRCA0kYIIWEhyzLKy8uxdetWvPjii+jRowfeeeedRHeLEEKISVEibUZvhACUNkIICZnPPvsMlZWVqKysRHl5OXbv3o2nn34a6enpqK2txe23346vvvoq0d0khBBCiM2gtBFCSIhkZmaiSZMmaNKkCZo2bYouXbrgkUcewezZswEATqcTzzzzTIJ7SQghxIwIgugpRhLyTeBQnbjgK4EQQiJk1KhR6Ny5MwDgf//3f+F0OhPcI0IIIWaD6ZEkEihthBASIYIgoHv37gCA6upqlJWVYf/+/Z6iJV9++SVOnz6Nf/zjH7jgggvQvHlzCIKAefPmaY5z+vRpvPLKKygsLETLli2RlpaGli1bYtCgQVi4cCFkWfbbhxMnTmDKlCn405/+hNzcXKSmpqJVq1bo0aMHbrnlFnzwwQdoaGjwaffTTz/hgQcewLnnnosmTZogLS0Nbdu2xR//+EeMHTsWS5cu9WlzySWXQBAEFBUVBb0ueo8TADp16gRBEPDkk08CAObPn4/LL78crVu3hsPh0D32J598guuuuw7t27dHRkYGmjdvjj59+uDZZ59FdXV1wL4QQkiiYSESEgks+U8IIVFAVK2l4y1XZWVl6N27N7Zt2+a3/fbt2zF06FDs27dPc//x48excuVKrFy5Eh988AHmz5+PrKwszT47duzApZdeimPHjmnuP3bsGI4dO4bt27fjgw8+wF//+lfk5eV5tq9duxZDhgxBVVWVpt2RI0dw5MgRfPfdd/jwww9x6tSp0C5CGMiyjFGjRuH999/3u095eTlGjhyJVatWae6vra3Fpk2bsGnTJrz55ptYuXIlzjrrrJj1lRBCIoEl/0kkMNJGCCFRYMeOHQCAjIwMnHHGGZpt9913H0pLS/HUU09h586dOHHiBL755htceOGFAIBDhw7hkksuwb59+9CxY0fMnj0bpaWlKCsrw86dO/HUU08hPT0dy5cvx1133eVz7jvuuAPHjh1DVlYWnnvuOezYsQMnT57EL7/8gk2bNuH555/Hn/70J00bSZIwatQoVFVVoWXLlpg9ezZ2796NsrIyHD58GOvWrcO0adPQtWvXGF0xF2+//Tbef/993Hrrrdi0aRNOnDiBXbt2YfTo0QCAhoYGDBkyBKtWrUJ2djaeeOIJbN26FSdPnsSBAwfw9ttvo23bttizZw+uvPJKRtwIIabF8Hy2MBbjJvaFkTZCCImQ+fPn44cffgAA/OUvf4HD4dBsP3ToEFasWIHBgwd77lOL3T333IMTJ06goKAA69atQ/PmzT3bmjdvjscffxwXXHABBg8ejPfeew/jxo3zSFhFRQXWr18PAJg+fTrGjRunOXfLli1x4YUXYvz48Zr7t2/fjgMHDgAA3nzzTVx11VWa7W3atEG/fv3w6KOPhnVNQuXQoUN4+OGHMWPGDM99Z5xxhkcWX3nlFWzYsAHZ2dlYv349/vjHP3r2a9GiBUaPHo2BAweiZ8+e2LlzJ15//XVMmDAhpn0mhBBC4g31nRBCwkCWZRw5cgSzZs3CbbfdBsA1h2vixIk++/71r3/VCJuaffv2YdmyZQCAl156SSNsagYNGoRLLrkEAPDPf/7Tc7+66Enbtm1D7r96fpuRdtGmefPmeOqpp/xunzlzJgDg/vvv1wibmvbt2+Oee+4BoL02hBBiJliIhEQCI22EEBIil156qd9tDocDzz//PAYMGOCzbciQIX7brVmzBrIsIyMjAxdeeGHA+WN//OMf8eWXX+Lbb7/13Ne8eXN06NABBw4cwKOPPopWrVqhf//+QR9L165dkZGRgdOnT+Pee+/FG2+8gfPOOy9ou2gzYMAAZGRk6G7bu3cv9u/f79kv0LU599xzAQDfffcd6urqkJaWFvW+EkJIJHBOG4kEShshhISJw+FAp06dcMkll+Dee+/1Kz2BimPs2rULgKtyZG5ubkjnPX78uObv559/HiNHjkRpaSn+8pe/oE2bNrj44ovRv39/XHbZZfjd737nc4ysrCxMmzYNDz74IL7++mv88Y9/ROfOnTXt2rdvH1J/IiGUawMAhYWFIR1PkiSUlZWhdevWEfeNEEKiCaWNRALTIwkhJEQ+++wzVFZWorKyElVVVWhoaMDevXvx1ltvBYxSeVd7VFNeXm64H6dPn9b8fd1112HNmjUoLCyEKIo4cuQI5s+fj//+7/9Gly5d8Oc//xkbN270Oc6ECROwaNEi9O7dG4ArVXPevHkYM2YMOnbsiEGDBmHnzp2G+2eEaF8bwPf6EEKIGXBJm9FCJJQ24oLSRgghIZKZmYkmTZqgSZMmAWXDCE2aNAHgKqohy3JINyVlUM2ll16K4uJinDx5Ep999hkee+wxT7GSjRs34pJLLsHXX3/t02748OH4+uuv8csvv+Djjz/Ggw8+iN///veQZRkrV67ERRddhB9//FHTRhCCDyL01oQzinJtAGDbtm0hX59OnTpFfG5CCIk2gmh8jTZKG1GgtBFCSAJR0gN//fVXlJWVRXy8Zs2aYdCgQZg6dSo2b96MNWvWICMjA3V1dZg+fbrfdi1btsSwYcPw7LPPYseOHfjggw8gCALKy8s9xUAUlDloNTU1fo93+PDhiB+LOnVSqc5JCCGEJCOUNkIISSCXX345AFc1yoULF0b9+AMGDPAUR1HPEQvG3/72N/z+97/XbdemTRsAwO7du/22X7lypdGu+tCjRw9PZcv58+dHfDxCCEkkrB5JIoHSRgghCaRr16648sorAQCPPvootm/fHnD/iooKHDlyxPP3iRMncPLkSb/7O51OTzqlem24n3/+OWA1xurqas95vBcLV+bAfffdd/juu+982v7yyy/4n//5n4CPIxQEQfCsL7dw4cKg5fydTif27t0b8XkJISQWcHFtEgl8JRBCSIJ57bXX0KpVK5SVlaF379545JFH8M0333iEbNeuXViwYAGKioqQn5+PDRs2eNqWlJSgffv2uOmmm/Cvf/0Lu3btQllZGX7++Wd88cUXGDZsGHbs2AEAuPHGGz3tVq9ejfz8fNx2221YsmQJ9u7di19//RUHDhzAp59+ioEDB+LXX3/1aQcAI0aMQE5ODgBg2LBhWLZsGU6ePImff/4ZH3zwAfr06eO3jL9Rxo0bh4svvhiyLOPmm2/GzTffjNWrV+PIkSP47bffsH//fnz++ed46KGH0LlzZ7z00ktROS8hhEQbRtpIJLDkPyGEJJj27dtj3bp1GD58OL7//ntMnz494Pwz7zXIampq8K9//Qv/+te//La5+eabcffdd2vuKy8vx9y5czF37ly/7SZNmoShQ4dq7mvRogVef/11jBo1Cj/99BOGDRum2d6uXTusWLECBQUFfo8bKqmpqVi+fDn+67/+C4sWLcI///nPgBE3rs9GCDErLPlPIoHSRgghJuB3v/sdtm7digULFmDRokX49ttvcfz4cciyjLy8PHTr1g39+/fHtddeiz/84Q+edn/+859RXFyMNWvWYP369Th48CB++eUXSJKENm3aoHfv3hg9ejSuuOIKzflGjhyJM888E2vWrMHGjRvx888/49ixYxBFEe3bt8ef//xn3HHHHejTp49uf//2t7+hffv2+Pvf/45NmzahqqoK+fn5uPrqqzFp0iTk5eVF7drk5OTgo48+wvr16/HOO+9g/fr1OHz4sGdtu3POOQe9e/fGlVdeGfJ6boQQEm/CSXdkeiRREGRZlhPdCUIIIYQQQuxIRUUFcnNzUTL6SuSkpRpqW1lXjx7vfIry8nI0bdo0Rj0kVsD2+l5fX481a9bgoYcewgUXXIBmzZohNTUVrVu3xlVXXYUVK1YkuouEEEIIIcTmcE4biQTbp0euXbsWl112GQCgdevW6NevH7Kzs7Fjxw4sX74cy5cvx9ixY/HGG2+EtGAsIYQQQgghRmF6JIkE278SRFHE8OHD8e9//xtHjhzBp59+igULFuD777/H/Pnz4XA4MGfOHLz//vuJ7iohhBBCCLErghDejRAkgbQNGDAAixYtQv/+/X22XX/99SgqKgIAvPfee3HuGSGEEEIISRYEIYz0SEobcWN7aQvG+eefDwA4ePBggntCCCGEEEIIIb7Yfk5bMPbs2QMAaNOmTYJ7QgghhBBC7ArntJFISGppO3r0KObNmwcAGD58uO4+kiRh//79SE1N1YSo09PTkZ6eHo9uEkIIIYSQAMiyjMrKSrRt2xaiSUWHi2uTSEhaaWtoaMDNN9+M8vJynHvuubjjjjt09zt8+DDOPvvsOPeOEEIIIYQY5eDBg8jPz090N3RhpI1EQtJK25133ok1a9bgjDPOwKJFi5CWlqa7X05ODgBg65z/QU5mhuf+tNQUpKcaWyBRA9c0Dx1ZSnQPzIXZroeQwC+UcM/tb2K33vG899X5ApX1jud9n9exNW28z6vepjqfvzay8n/3dtl7urKmXeP/ffqt8/hlBP+VVzm/4PXaFKDzOafz+hW8Pw8j/Xz0015ACO+dEM/t/Vh9jxP8XD6P2xspxPd6xNcrss+UoI8jyufTHovfpUYx/HxZhMrqGpxz4wOecZsZEUTjkbNEfsUSc5GU0nbfffdh7ty5aN68OVavXo0uXbr43VdJiWx7RnM0zc6MXids+qEZE0IduCQLlLZGwv0FMi7SJur/X29/zb7+z6cnbd7CprnP+3iCn2Pp9BEILGyyzv56IhOKuOkOIiN5nfuTtlCOGQ1pC7HvAQfPFhC2sAb/0f78Mtvnocmxq7CpMXO1RaZHkkhIOn+fMGECXn75ZTRr1gyrVq3yVI+MOyb+UDEVFDZfzPazW6IGTfFIGYnH+zTQ8xlClM2bWAqbLIieW9BzGyCo9PojQe8FChuFzYokg7ARYmeSKtL28MMP44UXXkBubi5WrVqFXr16JbZDgsCIGyF2xEiUTdPOmCTqRdl0jxUlYQu1T2qpkSH4RtsEMbQBt3JO730D9SXGUTYKG4XNalDWTIQoGv/BkXPaiJukkbZJkybh2WefRW5uLlavXo0LLrgg0V1yQXEjxBzEIWoTijB5iCTKFkVhCzd6FlXM0IcoQWGLAhS2kKGwmQtBML5YtpnTPUl8SQppe+yxxzBjxgxPSqRphE2B4kaIPQkkG4GKj4RAwCibzjmCCZuh6Jr6fp0BdDjRNlkQTD/AjDTKlnTCRllLKGZ/PyUjrB5JIsH20rZs2TI8/fTTAIBzzjkHr776qu5+eXl5eO655+LZNS0UN2KEUNPL4oUsxTcaYuYvMb/zvQxIWbSibCEeI+Tomm6hlgS+Fs1ShZDCFtVzxeV4NoayZl5YiIREgu2lrayszPP/zZs3Y/Pmzbr7dezYMbHSRnxhERJiAQzJmEIco2wxFTb1Nq9BdUjRtjgR0ny2GB7DysKWcFmL1TFtCoXN5AhhzGmzUXo4iQzbvxKKioogy3LQ2/79+xPdVVaUJMSmGCo+EuUoW6D2IQmba2Eh/8eNBJ0iLWFJsOcAYQ5Yg7SLJC2SwhYhFLaQEGSZwkaIzbF9pM1yME2yEVFktI3Yj3DWZFPhs5C2P9FSHyPI/LVAx/A9f2NbzSAxitE25RymH4RGImwhnyOJhY2EhOnfJ6SRMNIjwfRI4obSRogVMeMAKd7z2hJBNOfSGRG2kNYs0wqaX+kLJmwG5uT5FA/xV6I/EOHOiQu5vH6Q/cKNskX6HozHD1Jh9NEU1SFjfVybQFmzHoIgQjD4PWl0f2JfKG1mhNE2QuJPPKTT3/FDiLC5tnmnE3qlRQaJmKmFLRJZ09vuL+rmHW0zgqGKkjH4zIxE2BKeFklhszUUNosiCsYjZ4y0ETeUNrNCcSPE9EQ0/0ohmLDpilhoIhWSsEWj2iX8RN30lgMwWJBEV9yiNaCPkaQkhbBRqhICZc3asOQ/iQRKGzE3nNdmLZIhRTJUAlZbDFKWX+cYoUbZIhW2oHPp4D8C5S8yFjTaFiRFMmjEzc+2yCo+xmAuGIXNHMe3KBQ268OS/yQSKG1mhtE2QuxNoF9Q/QlbwPTJYBE4RfRCkzV/5f8DCVzYi2THe723AH0MNy2SwhYFKGw+UNYIIQClzfxQ3Ig3HNQkhhimqAQqPKInTkHnsulE2fwLWOiypt/eta+RyJTfFEkTLBpPYYvuOUx1fAtCYbMZgmA8G4XLQRE3lDZCSHRJkhTJUOd8GZ73FkjYQomyBRO2ANUljciaXlsf4YlSQRLNwNX7GOGkRkZZVqwmbKYqOBKv41sMypo9YXokiQRKmxVgtI1YjSQRNx9i+Zi912ULVDESOsKmkcEAVSS9zhcQP59LoaRImjHapit6FDYKVRyhrNkcUTSetcFCJMQNXwmEWAkOnlxEUpwmkIwEur6RFsTxli29L+Ig89iCpjgqUbQQhE0WRN9zqG+h4LVvsEhdJJE8/QOGIyAGInNmFjZZso+w8XMNAIUtGRAEIaxbuBw4cAD33HMPunbtiszMTGRkZKBz58649dZb8d133/ltV1xcjMGDByMvLw+ZmZno1q0bHn30UZw6dSrg+fbu3YuioiLk5+cjPT0d+fn5KCoqwo8//hiwXWVlJR555BFPP/Py8jBkyBB88cUXAdtJkoTZs2ejd+/eyMnJQU5ODnr37o05c+ZAtuH7idJmFZI5p5m/MlkTDsRCImiaom5VycBRNs0x/Aib5lhe51CEzt/Nb39iQMDUSL9tjMpMlOeDxUPYDBLW/DUKW1wQZJnCliwIYmO0LdRbmD92bdq0CT169MCrr76KqqoqXH755Rg8eDAEQcB7772HXr164aOPPvJp9+KLL+Kyyy7DypUrUVBQgKFDh6K8vBzPPPMMevXqhRMnTuieb8OGDTjvvPPw7rvvolmzZrjmmmvQrFkzvPvuu/jDH/6Ar7/+WrfdsWPH0KtXL0yfPh2VlZUYOnQoCgoK8Pnnn2PgwIGYNWuWbjun04kRI0bgzjvvRElJCS699FJceuml+P7773HHHXfg+uuvh2Sz6uMcDRNiFaw4uLFan02c0hlqiX91eX/1Pn6FTXV8v1Km05dglSX15tglHCMD4wCv3agMsOMkbGEJQbzet1b7fIgylDUSS8aOHYvKykqMHTsW+/btwyeffIIlS5Zg7969eOyxx9DQ0ICxY8fi9OnTnjZbt27FhAkT4HA4sGLFCqxduxYLFy7EDz/8gMLCQuzevRt33nmnz7mqq6sxcuRIVFdXY/LkySgpKcH8+fNRUlKCyZMno6qqCiNHjkRNTY1uP0tLS1FYWIi9e/di4cKFWLt2LT799FOIooj7778f27Zt82k3a9YsLFmyBO3atUNJSQmWLVuGZcuWYfv27Wjbti0++ugjvPbaa9G9qAnGRN+mJCjJHG0jxOyEsGB1yO099/mZxxYEWSe65n2/+tjhpi2GuhSB3/aI4DPNsIhEJy0y6CA7lF924yhsho+f5CIVLyhryYlSiMTozSgnT570iM60adOQmprq2SaKIp588klkZmbit99+w86dOz3bpk+fDlmWMXr0aAwaNMhzf1ZWFubOnQtRFLF48WLs2rVLc7558+bh8OHD6NKlC6ZNm6bZNm3aNHTp0gUHDx7Ee++9p9m2Y8cOfPLJJ3A4HJg7dy6ysrI82wYPHoyioiJIkoTp06dr2kmShBkzZgAAZsyYgc6dO3u2de7c2bNt+vTptoq2UdqINUj2FEkrD6Ri1fd4fBDHeGAVMDUy0Dw2A1E23ePqHFuGEPJN97g69+lWtDQgiFFLjYziPLaAWF3Y4omVP9MigNG1JEcQw7sZJD09PeR98/LyAAB1dXVYsWIFAOCmm27y2a9jx47o27cvAGDp0qWabcrfN9xwA0Sv8Zooirj++usBAEuWLNFt17dvX3Ts2NHnnEo/li9fjvr6es/9GzduxNGjR5Geno7hw4f7tBs+fDjS0tJw+PBhbNq0yd9DtxxJPhImhJAEEM6PECGmRepF2fQidbKqndGIl9/9LZQNkJDCI3EQNsNSkIjoWhIKG2WNAABEIbybQZo0aYL+/fsDAB577DGN8EiShCeffBI1NTUYNGgQ2rdvDwAoLS1FdXU1AKBXr166x1Xu37p1q+Z+5e9YtauqqsKePXt82hUUFCAjI8OnXWZmJgoKCnTPaWVY8t9qsPx/8mGHAU6yLgHgjT+p8YiYnyib0bRIQfQrbN7RtXBRl+yPZA023wOHH/0yEmUzeg6rCFusjk3Cg6JG1AiCCMHgd6Gyf0VFheb+9PT0gBG1N998E4MHD8acOXOwYsUK9OrVCw6HA1u3bsXPP/+MW265Ba+88opn/3379gEAmjVrhpycHN1jKoKn7Au4Kj+ePHkSANChQ4eA7Y4fP46qqipkZ2drjuOvXdOmTdG0aVNUVFRg37596N69e0jtlHNu3bpV01erQ2kj1kEU45MSR2KD3cVN5/FFvRiHwbRItbAFkrVQUxa9pciQuPlZf83vem2BiHAgbLy6ZAKEzW7pkIk6Z4KgrBFdwomcufdXxEfhiSeewJNPPum3WdeuXbFx40bccsstWLVqFX7++WfPtu7du+OSSy5B06ZNPfdVVlYCgEeo9GjSpAkArUAq7QK1VdopbZX9Qj1nRUWF7jmN9tXq2HgERYgNsNsgJ9qPx44SH2QRbX8iKKvmPmjmyqlTIr1SITVFSLzXadNZs013/pp3tM6r/0GXNPCD0UFvqFG2qBYeidXrj8JmWZgGSWLFwYMHUV5e7rlNnjw54P4bNmzAueeei5KSEnz44Yc4evQoysrKPPPDxowZgzFjxsSp9yQaMNJGrEUyRdvsOshJdMRNlk0x98pbZsKu4AjB/zw2dYVI+JGvUK6Fso8se9qq5SesaJkeoQhVyOmOJhG2GAqVaRfLNsM54wxFjYSCIIoQDM5pVvZXUgVD4bfffsM111yDEydOYOPGjejdu7dn25VXXonu3bvj3HPPxdtvv42bb74Zl156qSclsqqqyu9xlcW11f1Qp1L6a6telFuvbbjnNNrO6jDSRgiJP9EcxEVT4hMxuAxQfTHUKJv3fbKf//scW5E6iAFvjecIEnWLkoxHJcoWChS22JIESwgwskYMESijIYRsh1BZsWIFjh8/jrPOOksjbArq+4uLiwEAnTp1AuASPnXKo5qDBw9q9gVcAtWiRQsAwIEDBwK2y8vL06Q0Ksfx106dFqk+Z7B2/vpqdShthJgRmw90ACTHYzSK3pdzoPL5fqJsyrHUFSJd272KknhJmXoRbjVGxM0oASN0YctYCFG2ZBI2VoiMCZQ1YhhRcGUMGboZlzZFZgJFmXJzcwEAZWVlAFxz4JR10jZv3qzbRrm/Z8+emvuVv2PVLjs7G126dPFpt337ds3i4Ao1NTXYvn277jmtDKWNWI9kX7PNTkRrYGellNlQX78BBA4IUnzEax6b5373cdWypoiadhFunfvUgudn6QB/fY9aQZaQZIzCFu6xo4bNhY3RNRI2cYq0tWvXDgCwa9culJeX+2yvr6/Hli1bAMCzMHVaWhqGDBkCAPjwww992vz000/46quvAADXXHONZpvy9/z5830Ws5YkCQsWLAAAXHvttZptV199NQDX/Du9qJnSj6FDh2oWCL/ooovQunVr1NbWYvHixT7tFi9ejLq6OrRt21Y30mhVOPolxGzYfMBjaQIN2iMQkkDpjK77vCTIz5ps3sfxJ2yN+6vmvHndtMfVyptyLCOPK1SiPRiO2lIECRY2S6y/ppzXplDWSKQoc9qM3owyaNAgZGdno6amBrfffrtmTlldXR0eeOABHDhwAKmpqbjuuus82yZNmgRBEPDOO+9g5cqVnvurq6sxZswYOJ1ODB8+HN26ddOcr6ioCG3btkVpaSmmTJmi2TZlyhSUlpYiPz8fo0aN0mwrKCjAsGHD4HQ6MWbMGNTU1Hi2ff7555g3bx5EUfQpuiKKIiZOnAgAmDhxoqas/759+zBp0iQAwOTJk30W+7YygizzEygQFRUVyM3NxS+LZ6Fpdmaiu+OCT5m1IitGsPGAJyiRRmGMfDAHEg7vfnjvK/qpiqgp7uEnpVEQfNt7VXDUzjlT7esvLdJ7TTb3MYILm9dcN1WkzDtlUREf9YBVgPu1KsuN293tBFnyfE75tPX8LWnP42c/bSf1++Vvu/4+YUTZTCBssThu1LHp5xdFzRpUVNWg1bA7UV5ebrriE8pY8ujsR9E003cx6IBta06j9R1PG35cH3zwAUaPHo2GhgaceeaZuOCCC5CamorNmzfj559/hiiKePXVV3HnnXdq2r344osYP348BEHAxRdfjJYtW2LdunU4cuQIunbtivXr1yMvL8/nfBs2bMDll1+O6upq9OjRAz169EBJSQlKSkqQnZ2N4uJi9OnTx6fdsWPH0K9fP+zZswdt2rRB//79cezYMaxduxayLGPmzJkYN26cTzun04kRI0Zg6dKlyMrKwsCBAwG45uhVV1fjuuuuw4IFC2wlbfZ5JCS5sNGbkLiJdMBnROQDDcJCrFYY9YGcvzL9fqJsrv38p0V67nMfT0/YlCUAfNZt87pfXb7fI4jx/voIJmw6mFbYQoyChRXZSVR0zYbCxsgaiTrK0ixGb2Fw8803Y/PmzSgqKkJOTg7WrFmDzz//HCkpKfjb3/6GjRs3+ggbADzwwANYvXo1rrjiCmzbtg2ffPIJmjRpgsmTJ+Pbb7/VFTYA6Nu3L7777juMGjUKZWVlWLx4McrKyjBq1Ch89913usIGAC1btsTmzZsxadIkNGnSBJ988gm2bduGK664AsXFxbrCBgAOhwOLFi3CG2+8ge7du2PNmjVYs2YNCgoK8MYbb2DhwoW2EjaAkbagMNJmYuwWbbPhoCcs4hVxCzfaJqpFSV+gwoq0eZfq14myaSRK8JUw3ShbIGELcq11I2iebbIr2uYdUUNj5E0ThQsUadOJ5AWT52BRNlMLWwhYpjqkDaGoWRNLRNrefBxNswxG2qpPo/Xt/2PKx0XiC9dpsxr8MiF2J9HruMUTf+X4PX8HXpjaX7VIz34hCJveOQDXwFUWRAiy5FmHTW+NNghCwM8lzzEEIfTBMIUt9GMaOG5UsaGwUdZIrBEEEYLB7zej+xP7Qmkj1iWZFtpONiIRN0kKLdoW7UW2YyWbutUZ/Rcu0YugyXoROPgXNmWbnrhpzyU2zm3TtBUDpi/qbQt7wGwFYbOTrCXyvDGCskbihigYL+EfRsl/Yk8obYSYAZsNgqKCjSNugWRJnRrp2y60tEjPfRB1ha1xXpr/frgia8p293ncKY2u80qawa6uqKmicH4HxsFe+2HMZQuFiISN0TXLQ1EjCSGcOWo2/R4kxuErwUrwS4aQ0LBBBFZvLptmm0KAeWyhCJu/cv/qc2qWBvApWqK/Lpz+g1LNiQu0qHaohBllo7CFgU2EjcVFCCFWhZE2Ym3skCJpk8FQTFCuTTi/NIaSJukvRTJQlC/U9MsQCXUtM9+URz/VIv1E8byFTXdRbAWhMbIGNEbdvAe7huapKYcOlhppMK3S7zaj7ysrCBvTIcOGokZMQTiLZUczjZ9YGkobIcT8hJsqGS3Bivb8t3BRiZeCv+iXOsqmCJvPnDadRbq9C494z2eTBdHzfASSqEDz2ryrRvo/iGpduADFRyKex5YAYWN0LT5Q1oipEEXj30k2K1tPwofSZhX4xWNPbDAoihuxmuMWgZC5CnWE2DbYPDY/6BcW8bOItk5apOwleroFSfSKnKjmrylS5C/aBlmEIEiuwiT+Immy5Lugts+DjUIBEApb5Njgc4myRkwJ57SRCKC0WQF++RDiIhxxi3I6Y0h4IlGhS13QNEmdKJumrc4i3JolAKAVOeU+n3OrU1K9/m8k2ibIrjXc/Ebj9NZm02z3E0kLszBJzIUtFrIW4nGjBmWNkNjC6pEkApJC33fv3o1Zs2ahqKgI5557LlJSUiAIAqZNm5borgWHX0CEaAlnYBnOvMcga4HFhBAETy/K5tmmirI17i/4CJsM1X3qv73ukwSHjvjFYQAR4rWOqPAIhU17HosLGwuMEEugFJgydKO0ERdJEWl7/fXXMXPmzER3wzj8AgoNqxYjsfggKaFEUqBE93gmmbMGNEbUPKX9xZCibIHmsfkIm5fwaY6tfOx4FtJ2uvb1SpMERAiyM/jDiTA10l+UzSrCZnpZszCUNEJIMpEUkbYePXrgwQcfxD//+U/s3LkTt9xyS6K7RAiJBkYGncEG6kYGgGFF7owPMH1L/etE2XTmq4UqbC7JEyDLqptyn7JPANkL9niDpUZGjUQIWwjRqbDmrlHYAqJE1ChsxJIo1SON3ghBkkTabrvtNs3fohUq8fALiZDQMDLPzej8Nu9jB4vIxXlB8Ma5ad7FRvQrTKqlS4IIdeBLdv+GJ8uAAAkQ4Nrumc+mc34IoSqcLp6BdyjRNL/3J0jYgmDaUv4WljVCLA+rR5IISAppsxz8ciLEGEbSJQOJWxhpkoYqSEaKV/qjv7RIwCtCphNhg9woampc+yiFRgDI7n80xUca0yJlwTdNMhSpCvpQzShslLW4Q1kjtoLrtJEIoLSZCX45JQ8WHUCZnlAjXUYibv6OGY1jhIh3cRHdfQKlRXoJmyQ7PDLnHxECnO42/qNt3qjnrSkD7qALanseROD7QqkUGZaw2Tm6ZtHPGsoasSUs+U8igNJmFvgFReyAGQp6RJqiaIbHoMZ7jTY/UTagMS1Sv1KkMm9NWy1SOaYaEe6CI7KgSZOUIasKkwCCkt0oCBBkrVR5C5bfBbV1hS6E+0IVwTgImynXXbOgrFHUiO0RwkiPpLQRN5S2EKmsrtH8nZ6agvS01OgcnF9UkWPVCpJWJoT1tYISKzkKRdyU14vRL9AYS51P5UjNNp10xgBrr2nul92Spy7vD5fIeSMJIkS4FstW0iT1BtRKaqTPtrAqJoYYeQPiJ2xWWyjbgqIGUNYIISQUKG0hcs4tD2v+fvRvQ/HYLcMiPzC/rJIPiw6sYvJaVR8z2iIU6jw3vTRHbzELkiIZtXltXmuiabfpr8kGQD8tUpMi6RthU4RNN0VSdqdRQoQINKZJutuF/Ui9F9QOFFEzMI8tEcJGWYsMihpJSjinjUQApS1E9r7/D+RkZXr+Tk+N8NLxC4tYhXi9VvXOE40vq3DTJQOJW6Bom7Kfp2hHiEIXYB+fCJtXGqR6P59Fs4VGOdMTNk17CJ40Rk3Jf1kra3rFR5TnL5R5Z74PMNDcN4sLW6yFymLCRlkjSQ3ntJEIoLSFSE5WJppmZwbfMRD8siJWwgyv12hF4oKJm9GlAKJMoCIjmlL+6nRHnSib52/veWyqtEhJdrWXoCpOok6RdP9XlgUIguxuJ0IWZPdxZI+wBRW0UBbV1m2nI3HREDbKWkKgqBHihpE2EgGUtnjALyxiJcz6elX6Fe4XWLB0yXDTJKOdIqlGnS6pSZ1Ul/XXT4t0dd8lXIqgSd4pkrIASRVRA1wDbIcg+RQq0YvM+e22LOnMc/OTGuktaCG+/uIpbKaRNYoaIdaG67SRCKC0xRJ+aRFvzD7ossJrNtLoW6CoWyjiFux+9Tn8SJ4giuELnirCpjmlblqkzjw2lbA5IfoUIvFImVJ8RNCZX6fuTrDoVKAoW5hpkVEVtmhF1yhrFDWSUOK2XmYEuKr9GuunFR4XiQ+UtljALy5iNaz6mg1X4AJF3YKlSkaypICBypMaKfMSNdnnb9FPWqTgibKpI2VOWXufq2vuSJsgQ5JFiJBdVSSVRbbVfVOlYkI1t00jaO7USDWBCpB4rg/MIWwJj65R1AgJCoWGJBNJIW1btmzB3Xff7fn7hx9+AADMnj0bn376qef+pUuXok2bNqEfmF9WxA7Y5XUcTvpkqAtnB4u2BUmRFGQZMsKTPZ9S/nqpkX7SIrVpkKKusHlXkJRlAaIgwQkRkKGZ1wY0ioRStEQWRIhyveH0xpDSIkMRF3/CZsXomkVEDaCskcRhaVFTLeliqA0hSBJpq6iowKZNm3zuP3ToEA4dOuT5u7a21v9BZNk+g1tCFOz4mjYqb+GIWyjRtnAjcl4VIXUP7Y6s+fxflRYZKMImyaJG2nxVQYQAGZIguP/XGMHzznb0XlBbmc+mKUASpKCIbnn/UAqPRFnYKGuBoaiRRGFpUVPD6pEkApJC2i655BLI/LIhRIvd3xNGUicjibh5RduiiXcaJLzmQ/iU+/cq768UHpHQKGlqYXPK+mu1iZC0UTxZlXLpTokUIGuFDa4ftgRZDi5cfuayRSxslLWoQ1EjicI2oqaCc9pIJCSFtBFCvEi2gVgo0Td/89z8yZgf0fNJkYxkDhyg22dP1Ev5vyYN0uG36IgibJIsQgI0Iuc5HWQ4IUCQlehdo8Cp91E/3oBrtPmJsnmnRSZC2BIiayYXNUoaSRRJISeMtJEIoLQREi/MMlhL5kFZqPIWSNz00iT9RdtUx2qc1+YIra/e1SEF0b1emnYZAG16pHYemyJkSpVItbCpI26S3Bi1EwDIcAASkCICTkGEA07P8QGvRbXRmBap+dtb7DydDh5x0x47AmGLJLpGUSMk5iSFqKnhOm0kAihthCQTHJy5CCZvelE3f+KmQ8A128J4DrzTFzWVIvUqRqpK/UtQyZpK2Fw3NAqeu1uiCEiyDAEiZFluTI3UmWenOkPj4/JbGVInyhZgH9d+qmtldP5aJNG1aEgWRY0QXZJO1AiJEpQ2QkjyEoq8BRO3YNE2f8dx+EbcvAcz3mX/GxfS1kmZlLUSJ0GE0y1njfdphc0VbYNngW1X3wBBEABIcKAx/dIbpdiItoiI74La3lG2UNMigwqbGWWNokaILhQ1N1xcm0QApY2QZIEDNv8EkrdA4uZvH6iibYHmtLm3CbIE2U/apPci2ur7G2+qhbS9Svl7UiTV0Ta3sHkKkajSIyXIEAQg1SG795XhlEWkCHBF1dxioqkSKXvd711i0kvuYiJsiUqFNLGoUdJIoqGsaWEhEhIJlDZCCFHwJ2/+xM07TTJItE2ACPca1gFTKL1FTT2fTTc10ivKpk6LlGXBr7BJkmpOm2dxbbhWZJMESIIIpywhRZnvJsiA3ChbPosFeBUd8a4kqY7MxUPYAkqLDUWNkkbMACUjACxEQiKA0kZIMsDBnDH05M17npu3uHmnScJPtE0OrRhJKAOfQFG2RklTFyHxFTanJGhTJGUBKaIEyb0kgENulD8IjZUjfaJpATvqtTxAKJLlLWyJljUTiholjZgFilpoqAtHGWlDCEBpI4RYCX/FKPSIxjwA3XXZpODipt7m77ihoBQA8ZrPpom4KcVHVJUjnfCdx6ZE2xRhc6qicLIq0ibJACBCFAARMmRRtRacLHjSH5WomXp9Nk9qpDrK5q9ypHItlYcaBWGLqqxR0ggJCmXNIKweSSKA0kaI3bHiQM+InIV7jFClzl/ULZC4QfSNtun1z+EIOJ/NpyteqZEAGsv8exbMboysKaKmmdfmFja1uEnu4o8yBAiQ0eAU4BI32X0Or3XaNMVH3PPZAs4p858WGbCkf7xlzWSiRkkjZoWyRkj8obQRQhJPNCQt0nMGkzhveQskbsr+mmqTyjww0dh6bcrpdddn05/P5in7r4quubqjFTYlNbJxXpurh56H4GiMwAHQrBOnFTdVyqRXlE03LTIewhaqgJlE1ChoxOxQ1CLHe63NUNsQAlDaiF1IxKDfCph9IGim503dl0ACp7e4ttJeETeo5rdJEgRR1B3wuKJwfk6jrg7p/tL2pEbqLKCtjrJp12NTZM0dcVMJm6SKsjmlxo6IggxJcO/njsZ5ypso1SKVSpKyImoBnktNqX8/+wUStmjLmglEjZJGrAJlLYowPZJEAKWNEBJ/zCRregQTOHXUTV2gxDuypvpFVZBlV4QNcEXZ1ItRy17n8KkeqU6HFDxRNkl2aCNrXhG2xrRIEZJb1NTC5pTQGG2TlflsgCi4ZC7VIaLe4TqHKEgQIUGUnZ55bKLsVFWS9BNl8yNsHmkJNn8tUHXJAPsZ3h4jKGfEylDYoowghFE9ks8BcUFpI9bH7AJAGrHic6X02Z+86UXdvOe3eRUl8UTY1Its+xvcu4/vibB5FyBR5EwTcWtMi3T93yVqDZKvsEkSPCX/PR4pAJIso7ZBRHqK6DmXImyN89gaC5A0XhOtsGnuVz1+zbXVe/yhRNdMJmoUNGInKGzRh+u0kUigtBHrYkUBiCdmG0Ca8fnSqw7pD3/RN++om6Tax2t+myAq89lEhFL63xNdU+avuYXNtU3URNmUCFvjmmzutdYkV9TMO8LW4BQ8aZFOJctR9VAcooAGp/uhwyV1rsia3DiHTV2ARImyeeFdpCQcYTMka3EQNcoZsTsUBULMB6WNWA8zDv6DYYI5NAkjEc+XkUF1sH39VX4EfOVNXfbfE12TfNNh/AibZo6b0ChnnmbuSJs7UVETZVPLm0vQXGmRTllAgyS65a1R2JySe66bpMxpa3xoytS81BQlfVIVaXPPZ2sUOKlxzTZ/aZGqx6e5fsp1U18Xvf29r50eMXiPUc5IMkJhiyFcXJtEAKWNWAcrylqyE8/nLFYDbO/jqgc03vKmt16bUpjEnSapRNsEWYSsRK1kCTL8R908hUc8RUh8o2zqtdjU89iUaJsrHbIxsqa+T5YBp7PxoUoSIIlAZroy102EKLjkTJSdECSnj2wJsqwvbN6VIkMQtpBlLYqiRkEjyQ5lLfZ4L58SahtCAEobsQoUNusRj+csEQNt9TmVQY6mAImsTZVUV5RUl26WJdfkMbesCTripkmL9MxpU9ZWc0XbnNAKm/c8NqcSXXPPZ2twNgqb6/9QzWuTPQ8vVXAvEwABqaITDjSmRjYuru0VZfO5VhEKWwxEjXJGiC8UtvigfJYbbUMIQGkjZoaiFj6JHpjG+rmL9eNTi0GgL0z1JDB11M3TP5W4KXiWAGj82yV/ASJtgirSJguQVAtq+0TaPJE1V+GRBqeqYqSkFTanE+6omwxJVTfEVUVSRm29q32aow5p8ml3ARJXpM1TgMRflC0UYQsUXfOWszBkLekEzUyfmaEuXk9IMsH0SBIBlDZiPsw08CDGieXzF81BeDQWX9akQMKPvKnFTVVNUhA8KZKeY8gSFHlTfl1V/+uav+Zw/6sTZZNENHhujZG2BqdL2BqcrkibU9IKm9OpRNoAWZIhyUBDg+vh5DWVkSI4kSLVQZSdEGWn57qoo2x6wubBiLBFIGuWlTQ7fuYFe0yUOpKEsHokiQRKGzEXdhy8JFMRklg9f9EajEf7ufCOyHnLWwBxE2QZsjtF0rWGmw5KhM0zp60xuub0msfWoCo8okTWlEibkhKpFrYGp+wRN9ecNtld5NLVE9m9DIAyXvDMZ5MliJLTJ8qm232f6JlW2CKVtYRLmh0/r+IFpc40UAoIsQaUNmIeOACyNrF4/hIta1KQ84uqwY56kW3vlEBF1tTiJgmN0TZJgiBKPuImQ2yczyaIkGSHpnKkcmuQG6NrDZLoErUQhU1yyu77ZVV6pOs/GemqBb0hNBYgCSHK5pMWGaqwBXiuYiZp/OwxH8EWuCfEgnBOG4kEShsxB3YdNCVTlC2aRGNwHs61DyZpoewvqs8raqNuirg5HFAWppbVi1C7//X+5VsTbZMFT5StQZUOKcn6wqakRtY3uLrhlGQ0NMCdAil7ZM0pye6K/a75bRkZIlLc0+ycsmugoV1Y23+ULWRhC0HWwhI1u36eJCvezyclLmowyhZnBCH0tUHVbQgBpY2YAQ6wrE80n8NIhc2orBkRNX/HVv8SqhxPdFeQVCpGqsXNCdfUNXe0DX4WoFbmPyhVJJWKkeoom2cum1PQFTal4Igr4tYYYXM6XcImqf4vy675bLIk49QpCeUZInKzRWSKp5FxutItbHJoc9l0hE03uhaJrPGzIzlhFC4qUNgSQBiRNhYiIQqUNpJ4RNGegy9G2YxhRlmLpFiJ5P6i9UTevBbclhvTKNXVF2X3sZS1eRrXY3O4UyEdjSmRsoh6p+ievyZ6hK2+QZG2wOmQTkl2/e2UNXPaZNkVdSv7tR7tWqa4+yipiqXAN8qmm/aoI2wBomtBRc2OnxMkMhiFCwsKW2LgOm0kEihthJDIiMZAOhJhS4SshfKYlbGjE65fSkVV5UhRBJwNAADB6YqkaWruK91Q5rIJ2rlsDar0SKcsoN4pos7pK2wNDVph04uuudIi3fc7ZUiyO+ImyUhpEJGXXYsWtUdchUhUBUh8omze1yeQsIUqa5Q0YhRKXFAobImDc9pIJFDaCIkFiYyyxbOinpWELZisBTpWsMfpb8FtBRFueZPdaZOya16bJAGCE5AdgFuI1AKjrhqpTYd0uCNsrkibOsJW3+Cav+aSNjmk6JrTKbn/llRl/2UIAtAkrRZo0C6mHXAumwFh05W1cF9TsXjdc3BrfShxGihshFgXShsxB3ZNkbQziRS2RMpasD7rbXc6XQIgwpU2KbrntQGAKEJwOgExxV2UxJ0eqY6yqVIjG1TVIuucLmmra9AXNo+4BZE1WZYbpc0ddZMlGWfmpSHLUQahXnIvqN0YZVMeq6Yoidd11QhbIFkL5bWUiPL+kZ6TA2TzoanomlxQ2EyAgDAKkcSkJyQKvPfee1E71qhRo4LuQ2kjJNpwLltoJFrYoiFrhp5r0S1v7vlsDrijb+5iJFIDBDlNcx6lCImSGumUHWiQUlDvdEXa6hsEjbDV1bvSIRsaXLJW3+CbCim55Uwtay5Rk9wpkhIkSUaTpuk4o5lrtOBan01ujLIBvimRynVTlgQIRdjCkWIrEc5j4cCaxAAKmzmQIUKGwfRIg/uT+FFUVAQhSu8tShuxFoy2RU68BryRPk+xFrZwo2uhSITftsEek9OdGuk+piQBjhS3tIkQUmTITieQ6j6He2FtSXCnQ0opqhL/gjvKphW2+gbZFWlrkD03PVlT0iDVkTVF1iSnBKdTQvlJJ5o3yUCr0/s1BUg818Q7yuYtbF7pkAFlzU6iFilGrgUH4uHjKQpkbyhr5kKpCGy0DTEvZ599Nvr27Rt2+/Xr1+PHH38MaV9KGyHRhFG22BENYYu2rHmdSw7WR3dKpKDMbVMQRaChHoIj1bWANeBZWFuSHXDCAafsQL17Llu9W9jqVMJWW9eYDum6Sa5Im5esSd5pkLL678Z/8zu1QHZqvc/abJ4CJN7XLxRhMypr0Xg/2XkSf6Drx4Fe0sPBvvlgIRL70a9fP7z99tthtx89ejSljVgUK0fbkkXYEhFlC+XaxjO6pjqXRtS8+6B3TkGEDCcgCxCU/RvcKZKpDRohkgSXsDUowiY5UOt0oLZBRG29gLp6AbV1QF29jPp6GXX1jcLmdGr/lSUZDfVOSDI80TS1qCkVIyWnBFmSkN0kBRIa3HPZtKmRAHTnsumtw+Z3oe1g1ylaBDu2XQdEFLqkhsJmTljyn3gjGxgTUdqIuaCwRdAHm6aYWUHYJF9ZkdXH1hzTXZTECcCR4vo6lmVXimRDQ2OkTRBc0qbMY5McqGtwoK5BRJ1K2GrrGmWtvt4VXWuol9zC5vpXalBH2vSFTZYk1RptMjLTReRnHYdwSjsnTUmNBOCTFul5/Gph83cdzPCeAfz3w64yB4T2WcFBPyGEBGTjxo0488wzIzrG448/jrvuuiukfSltxDxQ2OyPEbE04/y1QMLmLWshRJhkpxOywwEhNRWCwwHU1wJOV5VGJcpWL6egzpmC2oYUT4StViVsLmmT0FDvkraGegn1DU5ITldkTZE3yf2vIm6y1ChvsvsxSKrHe/xELdJQ64qy6aVGqipIatIi9YQtmKxF8oNDrOTCT5Q0aVCeE8qb5WCUzbwwPdJe9O7dO+JjnHXWWTjrrLNC2pfSRhKPVWUNoLAlmkjK+fvsGyVhU8ua+/8ekXPvr7QXBHdFSacruiakpEJw1rt2FR1oQCrqpVScdrqE7XS9iNN1Ak7XAjW1MmprJXdapFvW6p2uKJtK1hrqna7oWoMEyen0CJwkNwqbXnpGbm4aUqQ6aNZmc+MRN0klaHrC5k/WohkV9j5WLAes3q+JZBhM2VnebFqMRHmvUt7MBwuRkEigtJHEQmFLHsyUvhmsIEa0hU2SXe0kl9wokS3lqIIoQHA64RBECFlNIECGU0hBnZSGmoZU1NY7UFMnArKAnAygRZYMhyDD4V6nW2pwpUvW1AqoqhbwWyVw8lcJJ36tR91pJ5wNbnFzOiE1SK7iIw1Oz2ORVY9PEAUIgojhvQ4jp+JoY5RNuU6ayJqfoiNeC2zrXmN/z4WacAbUlLjYYGd5symCLHPAbzI4p41EQlJJ20cffYRXX30V3333Herq6nDOOefgb3/7Gx544AGkpqYmunvJhZVlDaCwWRmjr70whc2vrEmSKy1S0pbRF+obAACO7CYAgHpHOhyOLLRrmoHcTBG52QJSHZ69AQiQZFllfoCoM0D7tbwBPx2uxQ8HTmPP/hrs3HMKx07UqSJtbtlyC5LD4YAgysitP+GqGonGx+qpIul5nNpqkfpz3IKsyxYI7/0jkbh4DF6TYX6c3eTNptE2BYqbuUhEemRdXR3eeOMNLFy4EDt27EB1dTXy8vJw7rnnoqioCNdff71Pm+LiYrzwwgv45ptvUFVVhY4dO2L48OGYPHkymjRp4vdce/fuxbRp01BcXIzjx4/jzDPPxMCBA/H4448HTAGsrKzE9OnTsXjxYhw4cADZ2dno3bs3JkyYgAEDBvhtJ0kS3nzzTbz99tvYsWMHAKB79+4YM2YMbr/99qitoWaUI0eO4JNPPsHu3btRUVGhm80iCALmzp1r6LiCbKRsiYW5//77MXPmTKSkpGDAgAFo0qQJvvjiC/z222/o168fVq1ahczMTJ92FRUVyM3NxS+LXkbTbN/tJAysLmyAOaXN7Gu0Ge1fpAVIQp3LFmKULaQ5bIGErcHpKvLR4ARkCVJdA2T3vwqO9DRkdGgHuf81SGnXDWmpDkiy63fWSL58JNm1yHaKw3WMk7/W4f+2lWPztt/w7dbf8GtFAwRRhCgKcKSm4nfndcb0Ad9qrokgOTU3OJ2e+/XWavOZ0+eN+jobHZREMshO9ADWTgIHJP56RgsbixuQHCl2FVU1aH3VHSgvL0fTpk0T3R0NyliyZMs3yAkgPXpUnjqFHj0vDOtxHTp0CFdccQV27NiBvLw89OnTB9nZ2Th48CD+85//YNCgQVi0aJGmzYsvvojx48dDEAT0798frVq1wrp163D06FF07doV69evR15ens+5NmzYgMsvvxzV1dUoKChAjx49UFJSgu3btyM7OxvFxcXo06ePT7tjx46hf//+KC0tRZs2bdCvXz/88ssvWLduHQBg5syZuPfee33aOZ1OjBw5EkuWLEFWVhYKCwsBuISzpqYGI0aMwPz58yHG+b09a9YsPPTQQ6ivr/fcp6iW8j0uyzIEQYDTPTUiVJIi0vbxxx9j5syZaNKkCdauXYuePXsCAE6cOIEBAwZg/fr1mDJlCp577rkE99Tm2EHWFATRnOIWa+L1HMbq2kaQFqmHnrDp7NSYfuiOTkl1Da75ZbV1kOoa0HC6zhN9yxo6CumdCjwf8nrRM6OIggDR0fj3Gc3TMKBfHi6/2FX1qvTHU/j3xpP4+rtTKDudjot652raN6ZCuoVMPZcNOhE2nyIsQZ5Po2mGynEjTZ9MxEA2Elk1I3aJvDHiRmxGTU0NLrvsMuzatQtPPvkkHnnkEU1WWXV1NUpLSzVttm7digkTJsDhcGD58uUYNGiQZ9+rrroKa9aswZ133ukjetXV1Rg5ciSqq6sxefJkPPPMM55tjzzyCKZPn46RI0di9+7dPgGSsWPHorS0FIWFhVi2bBmysrIAAJ999hmuuuoq3H///bj44ovxhz/8QdNu1qxZWLJkCdq1a4d169ahc+fOAIB9+/ahX79++Oijj/CXv/wF99xzT4RXMnTWrFmD++67D02bNsWECROwdu1abNy4EbNnz0ZpaSmWLFmC/fv34/7778d5551n+Phhf0KtXLky3KZxR3nxTJo0ySNsAJCXl4fXXnsNAPDKK6+gvLw8If2zPZJkL2FTsMOAy8oYjbJF8Br0F2Vzb/Q6tVeUzX1upZS+5J5LJjc4ITc40XC6DvVVp1F55Df8sv0I0v9wEQBtZC0WCRFK1A0AzumUjdE3dsBb/yjA7P85C1f//iiQkQNJaDQ9TWqk64F6/asSNuU976k6Kevf/KGeRxeISD9bgvUj1qiqchITYMfvKRVCIl/rBAAgQ/SkSIZ8C3OoPn36dOzatQtjx47FE0884TMNKCsrC3/84x992siyjNGjR3uETdl37ty5EEURixcvxq5duzTt5s2bh8OHD6NLly6YNm2aZtu0adPQpUsXHDx4EO+9955m244dO/DJJ5/A4XBg7ty5HmEDgMGDB6OoqAiSJGH69OmadpIkYcaMGQCAGTNmeIQNADp37uzZNn36dEhxfF/PnDkTgiDg//2//4enn34av/vd7wAAt99+O5599lns2LEDt956K95++23079/f8PHDHnUOHjwYXbt2xcyZM1FRURHuYWLOzz//jG+/daX53HTTTT7b+/Xrh/bt26O2thafffZZvLtnf2z+JQhBpLxZFaNpkd7N1a9tA1E2KBUbJfecMqcTUoMT9TX1qC6r1T1XrPPyRVGAQ3SdIy9XRPYZrdG0ex806Xoh0s5sD8HRmJQhqEXHq4pkY8RRAiRnCHIWROCSRd4ArcBZUeISff2ihc2/syhuiUUpRGL0ZpT6+nq8/vrrAICHHnoopDZ1dXVYsWIFAP3xcseOHdG3b18AwNKlSzXblL9vuOEGn3REURQ98+aWLFmi265v377o2LGjzzmVfixfvlyTbrhx40YcPXoU6enpGD58uE+74cOHIy0tDYcPH8amTZsCPOro8s0336Bnz55+lwJIT0/H66+/joyMDPzP//yP4eOHPdr8/e9/jz179mD8+PFo164d7rrrLpSUlIR7uJixdetWAECLFi00Jq6mV69emn1JlLD5l58Gilv0iMVctmikRUYhyib73KcqRCKKSM10YPM1N6KurAyywVz3aCEIjZLoyMxGen5XZP9xADJ+1wuOZq08aXBKARJNFUlPdE0VbdO76RFM3kIh0s8cM8ibAsUtcdj8u4viljhcJf+NRtuMS9uWLVtw4sQJtG3bFueccw6+//57PPXUU7jjjjswadIkrFixwicCVVpaiurqagCN42Jv/I2Xlb9j1a6qqgp79uzxaVdQUICMjAyfdpmZmSgoKNA9Zyz59ddfcfbZZ3v+VqKbNTU1nvvS09PRv39/rFmzxvDxwx5pbt++HV988QWuueYa1NbWYvbs2TjvvPNw6aWXYvHixXENRwZi3759AIAOHTr43ad9+/aaffWorK5BRVXjrbau3u++xI0oNt6SAbtH3SKNZEStHwlIi/Q5jVeUzW93fPuqd0xBFJCamYrsvEykVB1C6dhbUL56GeSGeldELkEDeEEQ3DcRjmatkPH7i5DZazBSO50LITPHtZM6yqYWtkApkcHkTff+OEXdlD6YYWBrRXGzCyYZw8QKQZYpbwkgkkhbRUWF5lZbq5+ZAQDbtm0DAOTn52PSpEk477zz8OSTT2LOnDmYMWMGrrzySvTq1QsHDhzwtFHGwM2aNUNOTo7ucfXGy5WVlTh58iQA/2Ntpd3x48dRVVXlc05/7Zo2beopvqI+Z7TG9tGmRYsWmsfXvHlzANBcZ8BVREW5ZkaIaIR5ySWXYNGiRdi3bx8effRRtGzZEmvXrsXIkSPRsWNHPP300zh27Fgkp4iYyspKAEB2drbffZTypYHSPM8ZNRGtrhvnuT278PPodtTuJJPAJULczPzla6RvwQap4VSLDNafaETZ/KRGNrbX75sgiq6qjSkOpGSkIiM3E5nNs5CeLqPi4/dx/OlxqPliCaSy4+5DSjGZ3xYKypIAQloGUvK7IqP3lUj/01/haHsOIDoaRc3pdKdGSr43QHutjIpbvDFDP6wmbma4ZtHCrvOxVVDc4ouyuLbRG+CSkNzcXM/Ne56XGkUItm7dihkzZuDuu+/G7t27UV5ejtWrV6NLly7YunUrhgwZ4kk7DHe8rLQL1Fa9TIBe23DPGenYPtp06NABBw8e9Pzdo0cPyLKMTz/91HPfqVOnsG7dOuTn5xs+flSqR7Zr1w5Tp07F448/jkWLFuGVV17Bxo0b8fjjj2Pq1KkYMWIE7rnnHr85nlZg73szkJPVWPEmPTUpCm/GBrW42fUL0W7VJeNR5j8W1ysGUbZIEQQRMpyeFEQxNQUOSYIgCp7InJjigCM9FairQe23X8C5fSMcbdoj5eweSOnQFTijLQTR4emjEOcfCjwCl3MGUrr3RUq3PpCO/ADngV2Qjh3wLHOgagCIgus+QXS9LpSUH39V+9T7aO6XQvthJFrVAP31I56E+pjNghmuWTRJgsqSAFhd0uQcPHhQU/I/PT3d777Kj3v19fW48cYb8corr3i2DRw4EKtXr0bXrl1RUlKC+fPn45Zbboldx5OIiy++GC+++CJ++eUXtGrVCkOGDEF2djYeeeQRHD16FB06dMC7776LsrIy3HDDDYaPH9VPodTUVNx4441Yu3YtJk2aBFmWUVdXh3/+85/485//jP79+8d1QiAAT4hXHa705tSpUwAQcP2LnKxMNM1uvKWncTHuqJBMEbhYkSy/lJokyuYvNVKZz6aL9+vbE2ET3YKWBkd6GlIy0xtvGWlwpKZ4BEn+9TgaSr5CXfGHqP34FdRtWIqG0s2Qjh+EXFvt9bCkuETlBFF0pU86UuDI74q0Pw9DxtX3Im3gzRCatdKW/PeOVkYScYvXHLdg/YgnVvsRyCwpptHCrj8wqmDULfbIshDWDWhMFVRugaRNnd54xx13+Gzv0KEDhgwZAsC1rpm6jdHxsvpc/toq7fy1DfeckY7to82IESNwySWX4D//+Q8AV7rkCy+8gIaGBrzwwgu4//77sWXLFnTs2BFPPfWU4eNHNVz0yy+/YM6cOZgzZw4OHz4MADj//PNx+eWX41//+hc2bNiAfv36YfHixbjqqquieWq/dOrUCQA04UpvlG3KviRBeA9srfwlabUBViDMEGWLxiLaBs4ZSZRNU4RED1GAIAuufx0Ozy9nYkpjeX0xRYTgcEBIcUAQhcb3huwqciI01EM6fhD49SicogNISQXSMyA0aQFk5ULIyoGYkQWkZUJIzYCQmgZBTAEcDkAQ/VajlD0FRNzpjc4GV0EUqcGzmDYysiFm6c938PS/6RlIL3RV/Tq9ZGZjeqQT7oiR03MtXHNBhcARN8A3csOImzXw/hxI9DWMBJtH3ACu5xZ7winhb/w1d9ZZZ+n+X2+fI0eOAGgcA//222+orKzUndemN17OyclBixYtUFZWhgMHDuiuP6a0y8vL06Q0durUCVu2bPGZ86WgzN/zPqfyf3/t/PU11lxwwQVYvXq15r7bb78df/rTn/DRRx+hrKwMv//97zF69Gjk5uYaPn5UpO2rr77CK6+8giVLlqC+vh6iKOLaa6/Ffffdh379+gEAnn76acyePRvjxo3Dk08+GTdpO//88wG48nv37dunW0Fy8+bNAKBZw42YADtJXKww6y+jZkyLDNanQFG2QMfSO64oeLxEQRAFQBZc425BhCzKEFMACfAtkawIm8N18+mTIoaS5BYeJ1BXC6n8GFBxAhBENAgqIVKV6BfcpfgFT2l+l5yhod51HEl2/e3+v+x0QnY2eOaryZLkEjmna505j+gBEJrlIa3HhUj7418gpLkrejkbvK6N6v9OAILcKG/qRbPVz6Eoaq+zMqhUXjuhLsatPl44mGEh6UDvFysInRmuYSRQ3EgEhFPCP5yS/z179oQgCJBlGSdOnPAU5VBz4sQJAI1zv7p27YqsrCxUV1dj8+bNuPTSS33a+Bsv9+zZE8XFxdi8eTOGDh1qqN2SJUs82/21y87ORpcuXTTtAFdRxNOnT/tUkKypqcH27dt1zxkrfvnlF/z0009IT09Ht27dNJHQnj17RqUfYX/ynD59GnPnzkXPnj3Rv39/zJ8/H9nZ2XjooYfw448/4qOPPvIIG+AalNx1113461//ip07d0bc8VDJz8/HBRdcAAD48MMPfbavX78eBw8eRHp6OgYPHhy3fhFiCcwuyvGKaOqlRvrBM79MEF2iptnoSouEKHgiaGKKA47UFM1NSHFAdDhc0TfRfRzvY6nXQnNHxwSn0yVlUgMESfm/0/N/wR1BE5S2zoZGQQv0mJRBqiC4UyJFQC2WqamuW00FGrauRc0H01HzwTM4/a8ZjX1U0LuGHhFVPR7Ndq+CEN6pd/Fe28y0P5aY/P2qxsrpk2b/XCSmJV7rtLVu3dozBlfSH9XU19dj7dq1AIALL7wQAJCWluZJmdQbL//000/46quvAADXXHONZpvy9/z5832qx0uShAULFgAArr32Ws22q6++GgCwYcMG3aiZ0o+hQ4dqFge/6KKL0Lp1a9TW1mLx4sU+7RYvXoy6ujq0bds25vU0SktLcckll6Bt27a46KKL0LNnT7Ro0QLjx4/XrC0XDcKWtnbt2mHs2LH4z3/+g+7du2P27Nk4dOgQ/v73v+savUKrVq1QV1cX7mnD4pFHHgEA/P3vf8eWLVs89588eRJ33303AOCee+4JK1RJSMKw6oDHKIFSDUMl2Fw2za4RDMi8xQpwSZcgeOTLdXOlP3oial430S1ugsPhaqsXQVG+GJWImVK1UZI8a6gp8qb837OumpLqqL4W3gtmez8mQZWmKQqN4paa4ha3FAgpqRDcoulDKOKmnN/fott66+3pyVvQdNsoDLqT5f0Xa6x6HSluJAziJW0A8MQTTwAApk+fjq+//tpzf0NDAyZMmIAff/wROTk5GD16tGfbpEmTIAgC3nnnHaxcudJzf3V1NcaMGQOn04nhw4ejW7dumnMVFRWhbdu2KC0txZQpUzTbpkyZgtLSUuTn52PUqFGabQUFBRg2bBicTifGjBmjWc/s888/x7x58yCKIiZPnqxpJ4oiJk6cCACYOHGiz3IAkyZNAgBMnjzZJ5Mlmhw/fhwXX3wx1q1b51p71X2rqanBzJkzMWbMmKieT5DDnKnucDhw5ZVXYty4cSgsLAy5XWlpKY4cOYKLL744nNOGzX333YeXX34ZqampKCwsRHZ2NtasWYPffvsNffv2xerVq5GZmenTrqKiArm5ufhl0ctomu27ncQRq3xJxi36E4fBjhXns4WSGhmgAIlG2vwVIVGvN6b622dxbVlyVYRUioJI7r/d9+tF7gQlsiaIqkhWCsTUVHd0K9WVMulwz2VT/i8IgCPFvTq2qJUs9bXxXk/NLXqe+51O1f1ej8XZuK+n78o1csuoqx8OCI4Uz7w99wNz/+segIii9n73MVQXQvV/1f2BvoCDpXR5y280vszNmEZmhTRJPcx4LQNh4zRJK6ZHVlTVoPVVd6C8vDyuxSdCQRlLfrt1B5r4WQPNH6cqK3HB+d3DelzTpk3DlClTkJKSggsvvBCtW7fGli1bsH//fmRmZuKjjz7yRNcUXnzxRYwfPx6CIODiiy9Gy5YtsW7dOhw5cgRdu3bF+vXrkZeX53OuDRs24PLLL0d1dTV69OiBHj16oKSkBCUlJcjOzkZxcTH69Onj0+7YsWPo168f9uzZgzZt2qB///44duwY1q5dC1mWMXPmTIwbN86nndPpxIgRI7B06VJkZWVh4MCBAFyRxerqalx33XVYsGBBTKVt8uTJmDFjBvLz8zF16lT86U9/QkVFBZYuXYqZM2fC6XTi+++/R/fu3aNyvrCl7ccff/Q7udGsLFy4EK+++ir+85//oL6+HmeffTZuvvlmPPDAA0hLS9NtQ2kzGVYQt2SXtmjPZ/M7r8xAARLvaEyAcwSSNtd/pdCkTWkfQNwaj+lqr6RTCg6HJ0InpKZ6ipL4SJtyE93RLeVftbh5XwPNAtjq/6sicCqJc4ma8ji89vdGEUV3RUlPRE4Uoidt6rZ6GBU3f1hd6KwobhYUBTuKmxWFDbCGtH2zdWdY0nbh+b8P+3GtWrUKL730EjZt2oTKykq0bt0ahYWFmDhxok/ETKG4uBjPP/88vvnmG1RVVaFDhw647rrrMHnyZL8LbwPA3r17MXXqVBQXF+P48eM488wzMXDgQDz++OM4++yz/barqKjA9OnTsXjxYhw4cADZ2dm48MIL8eCDDwYMDEmShDfffBNvvfWWZ+pV9+7dMWbMGIwdO9Zv0a1o8cc//hGlpaXYtm0bzjnnHM22p59+GlOmTMFzzz2H8ePHR+V8YUtbskBpMxmUNtV5kkDaolE1MpTUSKPSphzXj7R5juMlba77Vf/XeXzKXDdBEBpFTSlI4o5gaaTNnaaoRLhca6KphE0ZvMte/Za95FNqlDNN5M0ncihpH7saRdhE0bM2W1BpU/cxGtKmt7/PdoMD7UgH5okYBFPa4gOlzTRYQdo2bdkVlrT17tnNlI8r2WnatCl69eqFL774wmfbwYMH0bFjR/z3f/83Zs2aFZXzcYVoQqKJnYTNisRK6v0tlu5d5RBwiYdaxgQRgii5yjxLkquil7I4NbwqJAKNvwwq4uMPWQIkAXC4+yY43K8LSSlJ6d7Pq8iIImyav0N/PQmi6BI3vcGqnrBFA+9y+8Eq+AUrz2+0dL66qmU4JKJiYqiVNUlkJEE1SRI94lU9ksSHU6dOoWPHjrrblPoe1dXVutvDgdJGCNEn1lHNSATXpFXyPEKjoBI4QRQ04gYAcDg8C2Br0jhUFSMFpeKkP2QJgKMx+iWK8Iib3/1hTNQEEbIoAZJLEH0ep7KfXj/1irOEQqzXJAvn+JEO0BMlbxQ3QkwBpc1+BEvBjGZCI6WNEGJOYlE1Mlao10Lz3CU2ploKiuwIjQurKmubeaULepYJEMTG1ELVdg2e9EYZEN3RNrW4+UOdFhnsGulEDhVx80EvzdEIkuy/bbSjbUBixA2Iv7wx6kZCxKqpkVaB0kYigZ/gxFqYOQ3FpNEf22GkAEmiUIuHSsJc/zSu0aa+ee4XGtMLXfs3zk/TFSXv9cvU/1eXxPf+W9Mu+LXTCKTSR89G0UfYopYaGQmhSHs479tovdbivVYZP6Nig5k+ewghceXdd9+Fw+HQvQmC4Hd7SorxuBkjbcR66M0jIuYg1AFoJAVIYowmQhZOe1XqoOdYSrRKVRREb+FtAFrpCTViJbtTF0UJgOg7B8vfGmma+/WqQbrny6mjbUqf1I9HId7CFq35ROFG3IAonT+OkTczR91CiY6SmCLIMqNtMUSGAFlmpM1OxLOeI6WNEGJfdNIWo35s5UcE73O5RUcjboC+7KjboFHYNJE1IwMpZfAb6McNf4tpB0AjtKEIZbhpkgreMqU3qI9GmqTeuUIlmoUo1K+fWA+czSxvVsRGBUkobrFDggDJoIQZ3Z/Ej//93/+N6/kobYSQ6BCtKJvJ8VeEQ3cflbgB0MqbXjvd0vc6i2TroY62CaL/6E2g50n93ASQUM9jCfkxJHgwayVx8/QlTlEns8lbIoq1RAubiRvAOW7RhnPa7MXFF18c1/NR2kIl0g8uvUVuSXiYMTXS4iLigxmvcSLwLsIRDJXoeIuba7O+8GjSCXXmsvn0SUFWpUMqg0WlKInrIP4/b/TWo9N9TKrlDnQeiyGiMQAMJ9rmr53ufiYTNyC55Q2wlsDZSNwARt2ijSyHkR5pcH9iX+zzyRIPwv3g8m4nCNb6EjILkkSZIP5JxEBJb6Fo9WZRFXVSyZbgrgyp3Lz30aRFei9YHQjvHw9kKbT7jBDrtEhvgdTrq56IhvLZEOtocKw+o+JdrMRsP0JZ7YdOm31PCVa7/iZGRmO0LfQbMSvPPPMMVqxYEdExVqxYgWeeeSakfSltRjEiW8HkjPIWOjb7EiQWJNQIhNd7Witggv+be1/P/qGmRSpIXpEztfwoA3G9wXgokUQ/BUd08VdgxWpEIi6xErdklrd4P36iQZBlnxshyc5jjz2GxYsXR3SMRYsWYcqUKSHta9Fv0wQTimyFKmP84AsOhc38xPN1HAsJMBgZ0i0QEqBoSMDFseEla97t/X2WaKTMS9D09gl2DN2OBZEzP/IZdRIRbfN33lCJ1edWvL8zKG/hkQTfW5Q34yjpkUZvhACc0xYZ/irTMXoWPZLgi4+YgGgtMaBejsLr8yGYuDXuqJLAQOuzKajnYCnzaTT3RSklUD23LVQE/yIbM6I5vw0If45bqH0Jh0SUxjfjnDezf9fabH6bP1i0JHRYiMR+LFq0CF9++WXY7U+cOBHyvpS2SFEPzPiBFT0oa/6J9S+byXjtAxUcUW9TiYumimSgH3BCfb7Unx96Az2jg+VIZMMfRsQt0LmjWSI/3M9diluY543B6ypcrPDd6+/z1IYyx6IlwWEhEvtx6tQpnDp1KqJjCCG+byht0SCSQQPxxWrSYKbUIRIVIlpg23vxd+XzIZSovE6KZMgROvXabJ5FtUOMjhh5rOFE3Iwiyb6plv5kIdxqkv7a+t2X4tZ4XhOJG2DNSpPqzwgbChzRRwZg9NOTI0Xzsm/fvriej9JGCLEHiZZ9dVTNU35fR978EUjYjA6QvSVBT7IE0f82zX460cJg4ubd30QMpCluscVs4qbg81q1gMTZSOAYbQsMI232omPHjnE9n7U/HayEMnlafSMkHJL9CzERkU0/C0UHjYKJYuBBmLI91AhbsEIfRotsRHItBdH/Ld74e9yhijyLk4R5XpMVKdHDat+1NljahsVJCIkNjLTFGn542Z94pIvFi3gMFkK5XkYXtU4gPnPbAN/3fSi/nvuT8VAkSC/qofQpGr/cG5mbp9c2WoQT3WHELfaYNeqmYIW5b95YvIiJnrgxAsdCJCQyKG2xgKJGiHnxJ43RFMVA89j87av8Ge2BmlF5i7W4x2ogGg1pobhFcG6TixtgPXmL5g8vJoBVJpkeSSKD0hZNKGvJi52ibbEmlOtkgihbwGIkXs+3JtqmPYixc3oPztSD4FDXQPM3cI9UFMKJtsW9LH2MHnsssKu4AdaQNyuJg03lTU2yiBwjbSQSKG2hwnlo8cO7+h4hZkRH3ADoy1tIhwsgbNEiEeIWbcKN6JgtTdJIn4yS6IiSVaJuVhMFGxUs8SZZonCSbPw3SRP8hklMAqWNkGjBaJu9CTF90m/Uzc++fjb4ntsIgQak8RC3RA68ovHY4y1ugD2jblYQN8B68gb4/rBpE4mzu7wx0kYigdJGiNWIZaQj3ChnNCMwgcTIbFLsR9TDnpcWwiBX8LeP9yA5nAF7qM+993FjMfjVW6stVKw0v02B6ZKJw4rrvHmj9961sMj5q0BpV5kjJBQobYQQ4gefeW160bZoRVj9DWzDFZdARFsQQh1IReuc8SoCQnGL0vktEHVTsHL0zRsbplNaPRLHQiQkEuzxLiaEkHihJ1GRrE8WqG2kwhYo+un9y7zd5pEaeezhHsdn3yhcQ7ut5eY5v8VeX3abx26D9d/UCLJsyfXg9JbsDeVGCMBIGzEryq+CNvqSsQzJUAjGQHRMt4qkv/ltmvTEAMcPRfB0hM1vamQgQpnjZdfnO1pz++wUcQOYLmmERF+zaGOz6JvVxE2CAMngHDWj+xP7Qmkj5sbOA8pkJNJf2wPJVjReK0bWagu2b7gD01Cja3r7hbv4dDyI9gAx3nJkF3EDmC4ZDom+ZrGAAhd3mB5JIsH671Jif2zwZRI1LPClZEf8RriiPd8swPHCirKR6L5n7JIqCST+s0SWmDJpJmyWPmlWmB5JIoGjAGINKG7mxszfKkZ/HfcjTgHFLRJ5U9rbWdjCff9Ga4GiaM1vM3xeilvwPlhQFOw8klbkjQJHiOlgeiSxDkyVtDZWGpz5SX3Und+mbqMQSDYMCp6usMWiomQyE6s0ScAaqZIA0yXDwQzXLpbYLH3SDHCdNhIJlDZiLVigJPYYvbZ2/cXZDwHFTSFKUmX5CBsQ28GekcF+MNlKZnEDEj9ny4pFShTsLm8ABS5KSLLxBIJoJRwQ60NpI9YkWaNu0VzEOtkJVkEyQKGRkMQtQuI2jy6WRGNwF8ki27GE4hajPthA3oDEX8dYQoELnzAKkYCFSIgbvtuIdeGXReKxu0AmaJ6ZLSJsZiTY6zXWUWazz3EDzPOetlI6tR52nvemhnPgDMFCJCQSGGkjhNgffxFKA+u16R/WJVfRiLqFJGpmjDj5I14/qkR7PpTRaFaiIm6Avee5AdaOuimY5VrGg1i/Lm0A12kjkUBpI4SQQISwdpu3cPmTuIgiaHYVtlCuSTRTJEORLCuIG5Ac6ZKAdQuVqElGeQMocIREEUobIdEiXuk8sZzXZvUUl3DmOoYSbTOy6DZikN5oJWFLVihuscUOUTcgueQNoMB5EU66I9MjiYLtpe2zzz7DN998g//7v//D//3f/+HIkSMAgIMHDyI/Pz/BvSMRk6wFSaxIqKmIwQQp3JTGQLIbA3GLGlYTtkQMzGIRiQlHhihusccOUTcg+eQN8P2uTkKJk8MoRGK4cAmxLbaXtptuugnl5eWJ7gYhxA4oAhUPebOarMWaeKdIArGXIcBa4gaYQzLsEnUDkqfipB5JGIVjyX8SCbaXtmuvvRa/+93v0LNnT/Ts2RMtW7ZMdJcIMSfJsD5bpNE2hVhH3Shs5iHW89sA64gbwKhbLDGTGMebJBE4pkeSSLC9tL399tuJ7gJJBqxenjpeRFitMSTilTKrFqtoCly0hS2eA8BEDraMDuBjKR8Ut/hhp6ibQjJH34CkEThCjGJ7aSOEhEAyzQuMVrRNTaQCFy1Rs9PA1UzEY34bEF1xA5InXRKwp7wB5rvO8cZmAidDgGywhL/R/Yl9obQREg3iEUEijQS73sGibbEQN8+5/XzBesscUyCNE2xeWyyjbVYTNyD5om6A/VImFZI9+gbYopCJhDDmtMWkJ8SKUNpCpLLmtOaDMj01BelpqdqdmHhMrEi4UbZYLj0QjTljkaRJxkLCKWnWh+KmjxnFDbCnvAGMvilYMArHOW0kEihtIXLOLQ9r/n70b0Px2C3DtDuF+gHKdyCxC+GIW7SEKNLjBOs7o6fJgdmEQ8GK4gaY61raNeqmYMZrnigkyRJp/pQ2EgmmlbaHH34Yy5YtM9zurbfeQr9+/aLen73v/wM5WZmev9NTI7h0gT5g+e4k8cbOa93Z+bF5Y8XBaTh9jnaKpOHzxynaBlhP3ADzSbDdo24AUycthCQLkAyuu2Z0f2JfTCtthw8fxu7duw23O3XqVAx6A+RkZaJpdmbwHSNF7wOXImcN4hWZMdvrIZZpkkHPHeNrbvVoGwdwoWFUNKwsbkDyRt0Ae8sbYM5rTwiJCqb99Prggw8gy7Lh21//+tdEdz36CILvjbhIliiK2YnFazJac8ACDVBD6bfZB3mCaI4+xnNOSbD5jmYV7XB/3Ij244nX56bZfmACzPvaiDZKHp4Zn4MkRv20GLkRApg40kaCoAw2+W4myU48omGKFCViwGcGIUsG4hFtC+c8nnZRTvtM1nRJIHmibgpMnzQNnNNGIoHSZnXUH8B8Z9ufmFVrjMLcLyNpkqGKVqhVJCMRN6P9BuIjb8kyoIwV4UgOxS02mDVlL9nkDTDvc5EkyLLxwsgc2hEFSpudoMAlHqvPgbIrkazbprt/jOQtmQaPkRKsIIldsaq4AeaMugH2rzKpB6NvCUGWBcgGC4sY3Z/YF9tL29SpU7FixQqf+6+66iqkpaUBAHr27InXXnst3l2LLUyftB/J+lxGY822UAh3+QIgcnlLtgFjtEh0JUkg/tE2IDbiBjDqBiTne9Gsz4kNYXokiQTbS9sPP/yATZs2+dy/detWz/8zMjLi2aX4ksjKfsmKVaNtZi6PH4q4BbvusXx84T7nyThAVLDTY7eDuAGMugGUN8CczwshxLzVI6PFvHnzglac/PLLLxPdzdhi54qT8axYR6KLGQdFkbxPjFRxNEvFRzsQjyhsLInkR7VY/DgUzx9uzFwaz4o/vEULli2MGZIc3o0QIAkibUQFo27WJV7Pm5mjbfEi0veJWsa8B37xFDW7/lBjFCMRqUiuWSRRqmSOuAGMupkZzn2LKkyPJJFAaUs2KG7xwaopkvHGyHWK19w2IHrvk2Qe7CUj8ZYdhViJGxDfdEnAnGJAeXNBgYsYShuJhCT/BEpS+GFrPeL5nFk55TTYoMrIY+P7xDpEY7HtRD/fkY7MYvUjUbwj72YeocoSf4xTYPpkWDA9kkSChUdnJCISPUCxO1b/Yg9X3MJ5XRn59TreJd6tOh/Uin22C5FIDsXNhdmFwOqf79GE898Mob5cRm6EAJQ2QogZMHvaESWIxAuKWyNmHq0y6uYLDYOQmMI5bcmMXea3sXhGbAj3upr9dWXXx5XsmGHNNk9fIpzbFmlhjlg91njPcwPMPdcN4Hw3PTj3zS+SZPzrh8MbosBPmWTHLh+oVp6HRVyEOuiJRopkPNM/iTWItpAneqQVyygQo26+MPKmD3P8NDA9kkQCR7rEPlDczEMi5SZk+UuwuCnz5bxv0ThushKNgiRmIRojNTuKm9lHsFZ6jcUbWgiljUQER7nEXoM8M4ibnb604309rZJiFNEi3EHkLNJjk/AxW7TNCuLGqJsvjLoFJ0ltREIY1SOjdO6HH34YgiBAEARMmzbN737FxcUYPHgw8vLykJmZiW7duuHRRx/FqVOnAh5/7969KCoqQn5+PtLT05Gfn4+ioiL8+OOPAdtVVlbikUceQdeuXZGZmYm8vDwMGTIEX3zxRcB2kiRh9uzZ6N27N3JycpCTk4PevXtjzpw5kG362rLICInEHDsN9swgbsQar6lIXivhRMZC3T+Wx7Y7ZquPbXdxAxh18wflLThWeB6jiCzLYd0i5auvvsLzzz8PIcj3xIsvvojLLrsMK1euREFBAYYOHYry8nI888wz6NWrF06cOKHbbsOGDTjvvPPw7rvvolmzZrjmmmvQrFkzvPvuu/jDH/6Ar7/+WrfdsWPH0KtXL0yfPh2VlZUYOnQoCgoK8Pnnn2PgwIGYNWuWbjun04kRI0bgzjvvRElJCS699FJceuml+P7773HHHXfg+uuvh5ToFPUYwNEtsSd2FDcrlp+3Qn8jfa2E8ryE+9xZ4fqZkUDiFmwQbdcBpB3FDbDGoJ/yFhzmAsaM6upqFBUVoU2bNhg2bJjf/bZu3YoJEybA4XBgxYoVWLt2LRYuXIgffvgBhYWF2L17N+68807d448cORLV1dWYPHkySkpKMH/+fJSUlGDy5MmoqqrCyJEjUVNT49N27NixKC0tRWFhIfbu3YuFCxdi7dq1+PTTTyGKIu6//35s27bNp92sWbOwZMkStGvXDiUlJVi2bBmWLVuG7du3o23btvjoo4/w2muvRXbhTIgNR7YkbOw2QLSjuAH2e57MQDReK97z0qI1Ty2UuW98TZgbM0TbgPiIWyLlzexQ3kLDxvKWiDltkydPxp49ezBnzhzk5ub63W/69OmQZRmjR4/GoEGDPPdnZWVh7ty5EEURixcvxq5duzTt5s2bh8OHD6NLly4+aZfTpk1Dly5dcPDgQbz33nuabTt27MAnn3wCh8OBuXPnIisry7Nt8ODBKCoqgiRJmD59uqadJEmYMWMGAGDGjBno3LmzZ1vnzp0926ZPn267aJtNR7WEuKG4JZ5E9DWcuXHRfK3E4zFHs3iJHYkk2mZGrCJuAKNuwaC8hYYNo2+y1PjbRqi3SF4qX375JWbNmoVRo0Zh8ODBfverq6vDihUrAAA33XSTz/aOHTuib9++AIClS5dqtil/33DDDRC9vkdFUcT1118PAFiyZIluu759+6Jjx44+51T6sXz5ctTX13vu37hxI44ePYr09HQMHz7cp93w4cORlpaGw4cPY9OmTX4fsxWx6YiWhI0dB4B2Frd4PF/RikJZAbu+VmKN3a5bLAaJ0RAZq4kb5S0wFLfQscpzGoR4RtpOnTqF//qv/0KrVq3w0ksvBdy3tLQU1dXVAIBevXrp7qPcv3XrVs39yt+xaldVVYU9e/b4tCsoKEBGRoZPu8zMTBQUFOie0+rY7JuWED/YbVCpxipCFG/CrURp59dKsmG2aFuyiRuQ2PXqrDDIZ9TNGBaPvhmuHCk3foxVVFRobrW1tQHP9eCDD2Lfvn14/fXX0bx584D77tu3DwDQrFkz5OTk6O7Tvn17zb6Aq/LjyZMnAQAdOnQI2O748eOoqqryOae/dk2bNkXTpk19zhmsnb++2gGOTogvlADrEevnLJmibQDFjSQHySJuVhjgU96MY0GBiyTS1r59e+Tm5npu3nO91KxatQqzZ8/GDTfcgKuvvjpovyorKwEA2dnZfvdp0qQJAJc8ercL1FZp569tuOc02s4OpCS6A4TEDVFM7OAh1ghCbL+87H79CFEjy7H5oUGSIv9RIJp9k6X4rI+ofHYk6gcR5bPR7D8eKeJmlTUrzYLF5C0cDh486Ik8AUB6errufuXl5RgzZgzOPPNMvyXziTWhtBF9Yi0AxJpYTdwEMfxfr632WBOFlaOSwYQlVuIWDawobkB0pDUSzPycqqG82RJZkiEbXEtS2V+dLhiI+++/H4cOHcKCBQuQl5cX0jmUlEh1+qI3yuLa6j6oUyn9tVUvyq3XNtxzGm1nByhtxD8UN6KH1WSG4kbMRqLFRY94ixvAqFsoUN5shXqOmpE2Rli6dClSUlLw2muv+axVppTrnzt3LoqLi9G6dWvMnz8fnTp1AgD89ttvqKys1J3XdvDgQQDw7Au4BKpFixYoKyvDgQMHcN555/ltl5eXp0lp7NSpE7Zs2YIDBw7oPg5l7p73OZX/+2vnr692gNJGAkNxI3qEIzNWfR1R3OxNPGUl2kQ7ahTva5FoeaW8kTgTThZnOF+dDQ0NWLt2rd/t+/fvx/79+z2l9rt27YqsrCxUV1dj8+bNuPTSS33abN68GQDQs2dPzf09e/ZEcXExNm/ejKFDhxpqt2TJEs92f+2ys7PRpUsXTTsA2L59O06fPu1TQbKmpgbbt2/XPafV4bufBMcKX2hmIpFfqnyu9In0OTFbVMQOxK0Ihkl/LIjWDwHR/jEk3sUwErk0gIKV5kOxYImlkSQ5rJsRfvvtN8iyrHu79dZbAQBTp06FLMvYv38/ACAtLQ1DhgwBAHz44Yc+x/zpp5/w1VdfAQCuueYazTbl7/nz5/ssZi1JEhYsWAAAuPbaazXblAIpGzZs0I2aKf0YOnQoUlNTPfdfdNFFaN26NWpra7F48WKfdosXL0ZdXR3atm2L3r1761wh68KRCAkNLuJrDEHkL6Jmg+KWvAQb9HAQrMWqyyFEilXEDeBr1qLEc502o0yaNAmCIOCdd97BypUrPfdXV1djzJgxcDqdGD58OLp166ZpV1RUhLZt26K0tBRTpkzRbJsyZQpKS0uRn5+PUaNGabYVFBRg2LBhcDqdGDNmDGpqajzbPv/8c8ybNw+iKGLy5MmadqIoYuLEiQCAiRMn+iwHMGnSJADA5MmTfRb7tjpMjyTGYLqkMSKZT2V2rJg2GOnzYfQxq78wrHatSOyJVnpgLIprJCJtNNFz3QCmTJKkpWfPnnj++ecxfvx4DB48GBdffDFatmyJdevW4ciRI+jatSveeOMNn3ZZWVlYuHAhLr/8cjzzzDNYtmwZevTogZKSEpSUlCA7OxsfffQRMjMzfdrOmTMHO3bsQHFxMc4++2z0798fx44dw9q1ayHLMmbOnIk//OEPPu3uvfde/Pvf/8bSpUvRo0cPDBw4EABQXFyM6upqXHfddbj77rujf5ESDN/pxDhW+DLzRyIGA4y6mYtoR9xE0f8tUDs7YKXHZPdoWyx+TEvUNTHDDxxMmSQxwMyRNgB44IEHsHr1alxxxRXYtm0bPvnkEzRp0gSTJ0/Gt99+67caZd++ffHdd99h1KhRKCsrw+LFi1FWVoZRo0bhu+++Q58+fXTbtWzZEps3b8akSZPQpEkTfPLJJ9i2bRuuuOIKFBcXY9y4cbrtHA4HFi1ahDfeeAPdu3fHmjVrsGbNGhQUFOCNN97AwoULbRdlAwBBlq3yqZQYKioqkJubi18Wz0LTbN9fCZIeK758ErrQaxzOHc/nxMi1DKVfRq5PJHOVEjnAMcOANBpEZcH1OH+pikF+cPLXHyssXq8Qi74m8kcnswy8rPRjZZL+SFhRVYNW1/43ysvLTVfqXRlLPvLWSWRkGevb6eoKPHPbGaZ8XCS+MD2SRIbyRWZFeUsEypdpLKWBKazBsXPaaqwxyyA6Fli5kmQsSeR1SXSFSQWmTZIoEE5QlF9VRIHSRqID5c0YlIbIEYXIom2Jeg6sOBeQxJZoikmsFo9OtLgBlDejUN5MhwxXFUejbQgBKG0k2lDeQieW0mC2aJuZ+mIGrCpuZhg0xxo9OYmVCMUKO4obYJ6oG2Ct14T6e4YCl1DkMFa44O+7RIHvXhIblCUCrPKllihi+QWaDNc+2BylYHCuDgmVWP/wYBWJT/QI0gzruilYqViJAouWEGJZGGkLFaUCID/sjGO2qE8ywWtvbswecaNYarFUdCWGfU10xA0wX9QNsM5rA2DqZIJQFrk22oYQgNJmnHgUkrAjlAf/xPrHALtfe6vObVMwk7iZZRCcaAJJSSxlKNoikgziBpjndUt5I0GQZONfV5F8vRF7QWkLF8qbcTjfLXHEQtxCFQ0rPN9mEDfAPPJmV5TRT6RptcSFWQb8lLfIMYOEJwGyJEM2aGFG9yf2he/QSOHCycax0hcZsQZ2GYSbZdAZLxK2eHOEg6BY/hARbXGPx48mZvnx0mw/elhtzpsy380sz6cNMfvi2sTcMNIWLRh5M0Yio25mSkeLJ0yTDEyio20Kyfr6jDfBom52ijxYaS5epJgt6gZYN/IG2Oc9YBIkSYZk8HvK6P7Evtj63Xjs2DG89957uOmmm/C73/0OGRkZyMrKQrdu3TBu3Djs378/+idl5M0amOkLPZ5YadAQDoy4RUYyyqIZB0RWfB7M8IOHGjNeQyuGTRh5I8Q02HrkOn78eNx6661YsGABsrKycNVVV+HSSy9FWVkZZs2ahR49emD16tWxObkibxQ48yKK5pE3q71O7DSfTY2ZngczvT7tjj9x8zdYteKPH8mUJqlgpuUB1FDekhaleqTRGyGAzdMjW7RogaeeegpjxoxBu3btPPefOnUKt99+O+bPn48bbrgBe/fuRfPmzWPXEaZOmhsWgbAXdkmTVGC6ZGJJ1GLbsShpH49+mzGt1EzLA6hh2mTSEY77munriCQWW7/rXn75ZTz++OMaYQOAJk2aYO7cucjJyUFZWRlWrFgRnw4lUeSttq4e097/BLV19YF3NNOXVaK/1OP02qitr8e0Dz9FbX2Q58bKRGPRbe9bHKitb8C0BStRW9+g3cCoW2wJ8fVSW1+Paf/6zN7vnWiQgFFmbX09pv1zuf/nxqxRN8D2kTfXeODj4OOBJECS5bBuhAA2l7ZAZGVloWvXrgCAgwcPxvfkSSBvtfUNePqfy30Hn2YnCQbHtfUNePpfn4X/3MRy4GPm90UcBK62vgFPf7TK/3MTj9emWQe2icQ9OK2tb8DTCz53PT/xGEjF4rmI1wAwzuJWW9+Apz/8NPjnGuUtuoQgb7X1DXj6g2XWGw/EAKZHkkiwdXpkIOrr6z2FSNq0aZOYTqgHf4x/mwumpEVOor9oIk2TDITZUigJMUK8qkmaMVVSwYxVJhWsWO2TaZMhweqRJBKS9t01d+5cnDhxApmZmRg0aFCiu8PCJWYkEV/mfP55DYJhxkFmJFhFfvX6adVoWzwx+/Nr1sibFaNuAAuWEBJDkjLS9v333+Ohhx4CAEyZMgWtWrXyu68Slj584ldUVtd47k9LTUF6ampsO2rhDz7lWqmvmV/M/sUU7+chxuerrD6t+dcQRgY3kTyv0XxNxPJXyig/V5U1pzX/+iXWg8x4i2GiRT3EOW2VNbWuf9XvnXhERGL1fMQzmhPj5ziizzWFRL8OA2G1yJuCIBobD0SAcnwzpxOG4+ImfjgkzgiySV/dDz/8MJYtW2a43VtvvYV+/fr53X7o0CH069cPP/30E6666ip8/PHHEAJ8GB46dAjt27c33A9CCCGEEBJfDh48iPz8/ER3Q0NFRQVyc3Nxx98PIT2jqaG2tacrMHtSPsrLy9G0qbG2xF6YNtJ2+PBh7N6923C7U6dO+d129OhRFBYW4qeffsIVV1yBhQsXBhQ2AGjbti1++OEHpKamavZNT09Henq64f4RQgghhJDoIssyKisr0bZt20R3xS9yGNUgTRpbIQnAtNL2wQcf4IMPPoja8Y4dO4YBAwagtLQUAwcOxMcffxySdImiiLPOOitq/SCEEEIIIdEnNzc30V0IiCzJkA2m7Bvdn9gX00pbNDl+/DgGDBiAnTt3orCwEMuWLUNGRkaiu0UIIYQQQpIEShuJBBPPuo0OJ06cwIABA7B9+3YUFhZi+fLlyMzMTHS3CCGEEEIIISQkbC1tZWVlKCwsRElJCQYOHEhhMxmnTp3CWWedBUEQIAgCDh06lOguJSXHjh3De++9h5tuugm/+93vkJGRgaysLHTr1g3jxo3zrGdIYstHH32ESy65BM2bN0d2djbOO+88/OMf/0B9fX2iu5aU1NfXY82aNXjooYdwwQUXoFmzZkhNTUXr1q1x1VVXYcWKFYnuIvHi4Ycf9nyfTJs2LdHdIQDq6urw8ssvo1+/fmjRogUyMjKQn5+PQYMGYcGCBYnuXtyR5PBuhAA2T4+87bbbsG3bNgiCgBYtWuCuu+7S3e/qq6/G1VdfHd/OETz00EMUAhMwfvx4/POf/4QoiujRoweuuuoqVFVV4dtvv8WsWbPw9ttvY+nSpbjssssS3VXbcv/992PmzJlISUnBgAED0KRJE3zxxReYOHEili9fjlWrVvEHpzizdu1az2u+devW6NevH7Kzs7Fjxw4sX74cy5cvx9ixY/HGG28ELWhFYs9XX32F559/HoIgsHCDSTh06BCuuOIK7NixA3l5eejbty+ys7Nx8OBB/Pvf/0Z2djauv/76RHczrjA9kkSCraWtrKwMgKvyzsKFC/3u16lTJ0pbnFm9ejXeeOMN3HPPPXjllVcS3Z2kpkWLFnjqqacwZswYtGvXznP/qVOncPvtt2P+/Pm44YYbsHfvXjRv3jyBPbUnH3/8MWbOnIkmTZpg7dq16NmzJ4DG1O7169djypQpeO655xLc0+RCFEUMHz4c9913H/r376/ZtmDBAvztb3/DnDlz0LdvX4waNSpBvSQAUF1djaKiIrRp0wYXXHABPv7440R3KempqanBZZddhl27duHJJ5/EI488glTV2rbV1dUoLS1NYA8TgyzLhn9U4I8QRMG067QR+1JRUYEePXogJSUF33//PZo0aQLAnGurJDvV1dVo3bo1Kisr8f777+Pmm29OdJdsx4UXXohvv/0W06ZNw6OPPqrZtn79evTv3x/p6en45ZdfTF8ZLZm47bbbMHfuXBQWFqK4uDjR3Ulq7rvvPrz88stYsWIFFi5ciHfffRdTp07FY489luiuJS2PP/44pk6dirFjx2L27NmJ7k7CUdZpGzVlH9Iycgy1rTtdifemduY6bcTec9qIObn//vtx6NAhvPXWW8jOzk50d0gAsrKy0LVrVwAuqSbR5eeff8a3334LALjpppt8tvfr1w/t27dHbW0tPvvss3h3jwTg/PPPB8D3RaL58ssvMWvWLIwaNQqDBw9OdHcIXPNBX3/9dQCuaRCkESXSZvRGCGDz9EhiPlasWIF33nkHY8eOxYABAxLdHRKE+vp6z7zDNm3aJLYzNmTr1q0AXCmqnTt31t2nV69eOHjwILZu3Yobb7wxnt0jAdizZw8Avi8SyalTp/Bf//VfaNWqFV566aVEd4e42bJlC06cOIG2bdvinHPOwffff48lS5bg8OHDaN68Ofr3749BgwZBFBk3IMQIlDYSN3799VfcfvvtaN++PZ599tlEd4eEwNy5c3HixAlkZmZi0KBBie6O7di3bx8AoEOHDn73ad++vWZfkniOHj2KefPmAQCGDx+e2M4kMQ8++CD27duHpUuXcr6tidi2bRsAID8/H5MmTcI//vEPTbRoxowZOP/88/Hxxx8H/OyzIyxEQiKBP3OQuHHPPffgyJEjmDNnDvOyLcD333/vSW2ZMmUKWrVqleAe2Y/KykoACJgmrMz5rKioiEufSGAaGhpw8803o7y8HOeeey7uuOOORHcpKVm1ahVmz56NG264gYXETMbJkycBuDIJZsyYgbvvvhu7d+9GeXk5Vq9ejS5dumDr1q0YMmRI0i1pokib0RshACNtJAQefvhhLFu2zHC7t956C/369QMALFmyBB9++CFGjx6Nv/71r9HuYtISjedGj0OHDmHo0KE4deoUrrrqKkyaNCmSbhJiG+68806sWbMGZ5xxBhYtWoS0tLREdynpKC8vx5gxY3DmmWdi1qxZie4O8UKJqtXX1+PGG2/UVIgeOHAgVq9eja5du6KkpATz58/HLbfckqiuxh0JMiSDc9QkUNqIC0obCcrhw4exe/duw+1OnToFwFW6/K677kLbtm3xwgsvRLt7SU2kz40eR48eRWFhIX766SdcccUVWLhwIdehihE5Oa4qYlVVVX73UZ4rRqcTz3333Ye5c+eiefPmnogBiT9KMasFCxYgLy8v0d0hXiifawB0I9EdOnTAkCFDsHjxYhQXFyeVtDE9kkQCpY0E5YMPPsAHH3wQdvv169fj2LFjyM/PD5jGMmLECKSnp6OoqAhFRUVhny+ZiPS58ebYsWMYMGAASktLMXDgQHz88cdIT0+P2vGJlk6dOgEIXIFQ2absSxLDhAkT8PLLL6NZs2ZYtWqVp3okiT9Lly5FSkoKXnvtNbz22muabbt27QLgmo9bXFyM1q1bY/78+YnoZtJy1lln6f5fb58jR47EpU9mgeu0kUigtJG4cejQIRw6dMjv9q+//hoAcMkll8SpR0TN8ePHMWDAAOzcuROFhYVYtmwZMjIyEt0tW6MM/E+ePIl9+/bpVpDcvHkzAHgW3Sbx5+GHH8YLL7yA3NxcrFq1Cr169Up0l5KehoYGrF271u/2/fv3Y//+/ejYsWMce0UA12eVIAiQZRknTpzwFFNSc+LECQCNc3YJIcFhIRISc66++uqQ1h85ePAgZFnGk08+mbjOJiknTpzAgAEDsH37dhQWFmL58uXIzMxMdLdsT35+Pi644AIAwIcffuizff369Th48CDS09O5BlWCmDRpEp599lnk5uZi9erVnueLJI7ffvvN7/fJrbfeCgCYOnUqZFn2LFlC4kfr1q09c6b1Fp6vr6/3CPeFF14Y174lGlmSIRm8MT2SKFDaCElyysrKUFhYiJKSEgwcOJDCFmceeeQRAMDf//53bNmyxXP/yZMncffddwNwVV7Nzc1NSP+SmcceewwzZsxAs2bNKGyEGOCJJ54AAEyfPt2TRQO4IqQTJkzAjz/+iJycHIwePTpRXUwIrB5JIoHpkYQkObfddhu2bdsGQRDQokUL3HXXXbr7XX311SytHQOuvvpqjBs3Di+//DL69OmDwsJCZGdnY82aNfjtt9/Qt29fTJ06NdHdTDqWLVuGp59+GgBwzjnn4NVXX9XdLy8vD88991w8u0aI6SksLMTUqVMxZcoU9O/fHxdeeCFat26NLVu2YP/+/cjMzMS//vWvpFtKhnPaSCRQ2ghJcsrKygC4vhgWLlzod79OnTpR2mLEzJkz0bdvX7z66qv46quvUF9fj7PPPhuTJk3CAw88wLLyCUB5XwCueYXK3EJvOnbsSGkjRIfHHnsMF154IV566SVs2rQJ3377LVq3bo2ioiJMnDgR3bp1S3QX444sSZAlyXAbQgBAkKnwhBBCCCGExISKigrk5uZi+LgSpKbnBG+gor62Eotf7oHy8nIu/ZLkMNJGCCGEEEJIjFGKixhtQwhAaSOEEEIIISTmcE4biQRKGyGEEEIIITEmnGqQrB5JFChthBBCCCGExBhKG4kEShshhBBCCCExRoIESTZWDVICq0cSF1xcmxBCCCGEEEJMDCNthBBCCCGExBhZMp7uaDAwR2wMpY0QQgghhJAYwzltJBIobYQQQgghhMQYlvwnkUBpI4QQQgghJMZIkgRJMliIxOD+xL5Q2gghhBBCCIkxTI8kkcDqkYQQQgghhBBiYhhpI4QQQgghJMbIsgTZYDlIo/sT+8JIGyGE2Jx7770XgiCgf//+aGho8Nn+6KOPQhAE9OzZE6dPn05ADwkhxP4o6ZFGb4QAlDZCCLE9zz//PHr16oX169fjscce02xbuXIlpk+fjqZNm2LhwoXIyMhIUC8JIcTmhCNslDbihtJGCCE2Jy0tDQsXLkSzZs3wj3/8A59//jkA4NChQ7jlllsgyzLeeustnHPOOQnuKSGE2BdJlsK6EQJQ2gghJCno3Lkz5s2bB1mWccstt2Dfvn244YYbcOLECdxzzz0YMWJEortICCG2humRJBIobYQQkiQMGzYM48ePx8mTJ3H++edjw4YN6NWrF55//vlEd40QQgghAaC0EUJIEjFjxgx0794d5eXlyM7OxsKFC5GWlpbobhFCiO2RZQmyZPDG9EjihtJGCCFJxKZNm1BaWgoAqKqqwvfff5/gHhFCSHLA9EgSCZQ2QghJEk6cOIEbbrgBDQ0NGD16NARBQFFREX766adEd40QQmyPsk6b0RshAKWNEEKSAqUAyaFDhzBq1Ci8/fbbmDBhAn799Vdcf/31qK+vT3QXCSHE1kgSIEmywZvx89TX12PNmjV46KGHcMEFF6BZs2ZITU1F69atcdVVV2HFihUB2xcXF2Pw4MHIy8tDZmYmunXrhkcffRSnTp0K2G7v3r0oKipCfn4+0tPTkZ+fj6KiIvz4448B21VWVuKRRx5B165dkZmZiby8PAwZMgRffPFFwHaSJGH27Nno3bs3cnJykJOTg969e2POnDmQZftFKAXZjo+KEEKIhmeeeQaPPvoounfvjm+++QbZ2dloaGjAX/7yF2zcuBH3338/XnzxxUR3kxBCbEdFRQVyc3PR96rVSEnNNtS2ob4KG5ZdhvLycjRt2jSkNsXFxbjssssAAK1bt8af/vQnZGdnY8eOHSgpKQEAjB07Fm+88QYEQdC0ffHFFzF+/HgIgoD+/fujVatWWLduHY4ePYquXbti/fr1yMvL8znnhg0bcPnll6O6uhoFBQXo0aMHSkpKsH37dmRnZ6O4uBh9+vTxaXfs2DH0798fpaWlaNOmDfr164dffvkF69atAwDMnDkT9957r087p9OJkSNHYsmSJcjKykJhYaHnsdfU1GDEiBGYP38+RNE+8Sn7PBJCCCG6/Pvf/8bjjz+OrKwsfPTRR8jOdg0aUlJSMH/+fLRo0QIvvfQSPvnkkwT3lBBCSKSIoojhw4fj3//+N44cOYJPP/0UCxYswPfff4/58+fD4XBgzpw5eP/99zXttm7digkTJsDhcGDFihVYu3YtFi5ciB9++AGFhYXYvXs37rzzTp/zVVdXY+TIkaiursbkyZNRUlKC+fPno6SkBJMnT0ZVVRVGjhyJmpoan7Zjx45FaWkpCgsLsXfvXixcuBBr167Fp59+ClEUcf/992Pbtm0+7WbNmoUlS5agXbt2KCkpwbJly7Bs2TJs374dbdu2xUcffYTXXnstehfVBFDaCCHExhw/fhw33ngjnE4nXn31VXTv3l2zvUOHDpg3bx4EQcDo0aOxf//+xHSUEEJsTrwKkQwYMACLFi1C//79fbZdf/31KCoqAgC89957mm3Tp0+HLMsYPXo0Bg0a5Lk/KysLc+fOhSiKWLx4MXbt2qVpN2/ePBw+fBhdunTBtGnTNNumTZuGLl264ODBgz7n27FjBz755BM4HA7MnTsXWVlZnm2DBw9GUVERJEnC9OnTNe0kScKMGTMAuCoid+7c2bOtc+fOnm3Tp0+HFE5+qUmhtBFCiI0588wz8fPPP0OWZc8XtTdDhw6FJEkoKytDp06d4to/QghJFsxSiOT8888HABw8eNBzX11dnWeu20033eTTpmPHjujbty8AYOnSpZptyt833HCDTzqiKIq4/vrrAQBLlizRbde3b1907NjR55xKP5YvX66Zd71x40YcPXoU6enpGD58uE+74cOHIy0tDYcPH8amTZt8tlsVShshhBBCCCExxiwl//fs2QMAaNOmjee+0tJSVFdXAwB69eql2065f+vWrZr7lb9j1a6qqsrTZ3W7goICZGRk+LTLzMxEQUGB7jmtTEqiO0AIIYQQQojdaairhGwwXc/ZUAXAVcxETXp6OtLT0w334ejRo5g3bx4AaKJU+/btAwA0a9YMOTk5um3bt2+v2RdwVX48efIkAFe6faB2x48fR1VVlWdetXIcf+2aNm2Kpk2boqKiAvv27fOk9wdrp5xz69atmr5aHUobIYQQQgghMSItLQ2tW7fG5jUjw2rfpEkTj/goPPHEE3jyyScNHaehoQE333wzysvLce655+KOO+7wbKusrAQAj1D56wegFUilXaC2SjulrbJfqOesqKjQPafRvlodShshhBBCCCExIiMjA/v27UNdXV1Y7WVZ9inNH06U7c4778SaNWtwxhlnYNGiRUhLSwurPyQxUNoIIYQQQgiJIRkZGbrzr+LFfffdh7lz56J58+ZYvXo1unTpotmupERWVVX5PYayuLZ6vTh1KqW/tupFufXahntOo+2sDguREEIIIYQQYlMmTJiAl19+Gc2aNcOqVas81SPVKJWDf/vtN03Koxql2qS6ynBOTg5atGgBADhw4EDAdnl5eZqURuU4/tqp0yLV5wzWzl9frQ6ljRBCCCGEEBvy8MMP44UXXkBubi5WrVrlt1Jj165dPeukbd68WXcf5f6ePXtq7lf+jlW77OxsTWRQabd9+3acPn3ap11NTQ22b9+ue04rQ2kjhBBCCCHEZkyaNAnPPvsscnNzsXr1alxwwQV+901LS8OQIUMAAB9++KHP9p9++glfffUVAOCaa67RbFP+nj9/vs9i1pIkYcGCBQCAa6+9VrPt6quvBgBs2LBBN2qm9GPo0KFITU313H/RRRehdevWqK2txeLFi33aLV68GHV1dWjbti169+7t9zFbDUobIYQQQgghNuKxxx7DjBkz0KxZs6DCpjBp0iQIgoB33nkHK1eu9NxfXV2NMWPGwOl0Yvjw4ejWrZumXVFREdq2bYvS0lJMmTJFs23KlCkoLS1Ffn4+Ro0apdlWUFCAYcOGwel0YsyYMaipqfFs+/zzzzFv3jyIoojJkydr2omiiIkTJwIAJk6cqCnrv2/fPkyaNAkAMHnyZJ/Fvq2MIMty9FftI4QQQgghhMSdZcuWYdiwYQBcC1QrC017k5eXh+eee05z34svvojx48dDEARcfPHFaNmyJdatW4cjR46ga9euWL9+PfLy8nyOtWHDBlx++eWorq5Gjx490KNHD5SUlKCkpATZ2dkoLi5Gnz59fNodO3YM/fr1w549e9CmTRv0798fx44dw9q1ayHLMmbOnIlx48b5tHM6nRgxYgSWLl2KrKwsDBw4EABQXFyM6upqXHfddViwYAGljRBCCCGEEGI+5s2bh9GjRwfdr2PHjti/f7/P/cXFxXj++efxzTffoKqqCh06dMB1112HyZMn+114GwD27t2LqVOnori4GMePH8eZZ56JgQMH4vHHH8fZZ5/tt11FRQWmT5+OxYsX48CBA8jOzsaFF16IBx98EIWFhX7bSZKEN998E2+99RZ27twJAOjevTvGjBmDsWPH+iyTYHUobYQQQgghhBBiYuwTMySEEEIIIYQQG0JpI4QQQgghhBATQ2kjhBBCCCGEEBNDaSOEEEIIIYQQE0NpI4QQQgghhBATQ2kjhBBCCCGEEBNDaSOEEEIIIYQQE0NpI4QQQgghhBATQ2kjhBBCCCGEEBNDaSOEEEIIIYQQE0NpI4QQQgghhBATQ2kjhBBCCCGEEBPz/wFRZ5x4cAgJeQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAzsAAAFICAYAAAB3BuBpAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAACGgklEQVR4nO2deZgU1dn276qeDQYYQBSQRVQUNPgpKgYFEzKoUVQk4TVR3MAFcQmLqOCC+4ZRIwhurygxLoASEAKKLBGDJIjKa1xREXHYVECGdWa6u+r7o7t6qruruquqa+/7d111zXTXOadOLV117nqWI8iyLIMQQgghhBBCQobodQcIIYQQQgghxAkodgghhBBCCCGhhGKHEEIIIYQQEkoodgghhBBCCCGhhGKHEEIIIYQQEkoodgghhBBCCCGhhGKHEEIIIYQQEkoodgghhBBCCCGhpMTrDhBCCCGEEBJm6urq0NDQYKluWVkZKioqbO5R8UCxQwghhBBCiEPU1dXh4CbN8DPiluq3a9cO69evp+CxCMUOIYQQQgghDtHQ0ICfEcdfKw5DU5MRJPsg4bKt36KhoYFixyIUO4QQQgghhDhMZUkElULEVB1BtmYNIo0wQQEhhBBCCCEklNCyQwghhBBCiMMIpSIEwZydQZBlh3pTPFDsEEIIIYQQ4jBiRIAoCubqSObKk2wodgghhBBCCHEYoVSAYFLsCBQ7BUOxQwghhBBCiMOIJbTseAHFDiGEEEIIIQ5Dy443MBsbIYQQQgghJJTQskMIIYQQQojDiBEBYsSkG1uclp1CodghhBBCCCHEYYSIAMGk2BFAsVMoFDuEEEIIIYQ4jCXLDsVOwVDsEEIIIYQQ4jCCaCFBgUyxUygUO4QQQgghhDiMEBEhRMzlBhMgO9Sb4oHZ2AghhBBCCCGhhJYdQgghhBBCHIYxO95AsUMIIYQQQojDCAInFfUCih1CCCGEEEIcRojAtGVHYMhOwVDsEEIIIYQQ4jCW5tlhNraCodghhBBCCCHEYQRRhCCazMZmsjzJhkeQEEIIIYQQEkoodgghxALTp09PBJtmLBUVFWjbti26d++O888/HxMnTsTXX3/tdXcdRdn36dOne90VQgjxLcqkomYXUhgUO4QQYiP19fX48ccfsXbtWrz++usYP348unXrhjPOOCP0okeLoUOHQhAE9OvXz+uuEEKIpyipp80upDAodgghpEAWLlyI3bt3Y/fu3aitrcWGDRuwcuVKPPbYY+jZsydkWcbixYvRs2dPzJs3z+vuEkII8QBadryBCQoIIaRAmjRpgmbNmqU+t2jRAp07d8bJJ5+MMWPG4KWXXsLVV1+NvXv3YsiQIXjvvfdw7LHHethje5Fl5kYlhJB8CIKFBAUC7RKFwiNICCEOc/HFF6fiWfbu3Ysbb7zR2w4RQghxHVp2vIFihxBCXOD888/H6aefDgBYsmQJPv74Y81y69atw+jRo9GjRw+0aNECTZo0QdeuXTF8+HCsXbtWt/1+/fpBEAQMHToUAPCvf/0LgwYNQrt27VBeXo5DDz0Uf/rTn/DDDz/otiHLMl599VUMGDAA7du3R1lZGaqqqtC1a1ecfvrpePjhh/H9999n1dNKUKAkcPjrX/8KAFi+fHlWMgcljufyyy+HIAjo0KED4vF4rsOIv/3tb6n6n3/+ec6yhBBCCMUOIYS4xBVXXJH6f/HixVnrJ0+ejKOOOgqTJk3CZ599ht27d6Ourg7r1q3D//7v/6JHjx544YUX8m7nL3/5C/r164c33ngDP/zwAxoaGvDdd99hypQpOOmkk7Bp06asOvF4HL/73e8wZMgQvPnmm9i6dSui0Sh27dqFdevWYcmSJRg3bhxmzZpV2EHQ4MorrwQAbN68GYsWLcpZVtn/X/7ylzj66KNt7wshhDgFExR4A8UOIYS4RJ8+fVL///vf/05b9/TTT2PUqFGIRqM499xz8dZbb2Hz5s3Ytm0b3nnnHZx11lmIxWK48sorsXTpUt1tvPvuuxg7diwGDhyIFStWYNu2bfj2228xYcIECIKA77//HjfddFNWvenTp+ONN94AAFxwwQV49913sXHjRuzYsQNffvklXn31VVx44YUoLy83tK8XX3wxdu/ejYsuuggA0Ldv31QSB2V58803AQCnnHJKSrg8//zzum2uX78e77zzDoB04UgIIUGAbmzewAQFhBDiEh07dkRFRQXq6uqwZcuW1Pdbt27FmDFjAAC33nor7r///rR6v/71r/GrX/0KF154IWbOnIkxY8bgv//9r+Y21q9fj6uuugrPPvts6rsDDjgA99xzD3bu3IknnngCs2fPxq5du9CiRYtUmYULFwIAjj/+eLz66qtpbbZq1QrdunXDBRdcYHhfS0pK0KxZM5SUJB4zkUgkLYlDJldccQXGjh2L+fPnY/v27TjggAOyykyfPh2yLKNp06am+kIIIX5AEC0kKDBZnmTDI0gIIS7SsmVLAMDPP/+c+u7pp59GXV0dDjnkENx9992a9QRBwMSJEwEAn3zyia7Yadq0KR5++GHNdcOGDQMANDQ0ZMUMxWIxAED79u2N74yNXHrppSgrK0NDQwNeeumlrPWyLKfif84//3w0b97c7S4SQkhB0LLjDRQ7hBDiIkqaZkFofIAtWbIEAFBdXY26ujrs2bNHcznggAPQpk0bAMDq1as12+/du3dKUGXSrVu31P9bt25NW3fccccBAN58801MnjwZe/futbR/VmnTpg0GDRoEAJpxSUuXLsWGDRsAJBIaEEJI0KDY8QaKHUIIcZHa2loAQOvWrVPfffnllwASg/zmzZvnXLZt2wYA+OmnnzTbP/jgg3W33bRp09T/+/btS1s3ZswYdOrUCZIkYdSoUWjTpg2qq6tx55134p///GfK8uMkSqKCjz/+GB9++GHaOkUAde3aFb/61a8c7wshhJBwQLFDCCEu8f3336Ourg5AuihRBJAZlHYyiUQihupnTgTasmVLrF69Gtdddx1atmyJuro6/POf/8Q999yD6upqdOjQAY8++igkSTLdV6Ocdtpp6NKlC4B0605tbS3mzJkDgFYdQkhwoWXHGyh2CCHEJVauXJn6/5RTTkn9rwTu33DDDZBl2dBy11132d6/tm3bYsqUKdi2bRtWr16NJ554Ar/73e/QpEkT/Pjjj7jxxhsxevRo27erIAhCSsy88sorqK+vBwC8+uqr2L9/PyKRCC677DLHtk8IIU6SEC+iyYVip1AodgghxCWmTZuW+l+ZYBQADjvsMACJCUX9QCQSwYknnojrr78ef//731FTU4OTTz4ZADB16tSUK50TXH755YhEIvj5559T1hzFynPmmWfmdNMjhBA/I4jm59ih2Ckcih1CCHGB1157LZWI4Mwzz8QvfvGL1Lrf/va3ABKJCrZv3+5J/3JxwAEHpFJjS5KEr7/+2nDd0tJSAIlJS43QoUMHnHnmmQASIuezzz7D+++/D4AubISQYEM3Nm+g2CGEEId5+eWXMXToUAAJl7U///nPaeuvu+46VFRUYO/evRg2bFjKfUsPJaGBneRrU2110poDRw8le9zmzZsN11ESFSxZsgT33HMPAODAAw/Eueeea7gNQgjxG+Zd2MzPy0Oy4aSihBBSIPv378eePXsAJCwftbW12LRpE/7zn//gb3/7Gz766CMAQGVlJWbOnIkePXqk1e/QoQMmT56M4cOHY/78+TjhhBNwww034Fe/+hXatGmDuro6bNiwAatWrcLs2bPx0UcfYffu3bbuw1lnnYW2bdvi/PPPxymnnIJDDz0UpaWl2LJlC+bMmYP77rsPQGLS0SOPPNJwuyeeeCIA4Ntvv8Wzzz6bNkeOIAiaCRXOOecctGvXDlu3bsWsWbMAAJdccknKSkQIIYQYhWKHEEIKZMCAATnXC4KAM844A1OmTEHXrl01y1x11VWIRCK4/vrr8dlnn+GKK67Qba9Vq1YF9VcLWZaxatUqrFq1SrdMly5d8Oqrr5pq95xzzkG3bt2wdu1aXH311bj66qtT637961/jnXfeyapTUlKCoUOH4qGHHkp9Rxc2QkjQseKWRje2wqHYIYQQGykrK0NVVRVat26NHj16oFevXhg8eLCuyFFz+eWX4+yzz8bTTz+NRYsW4auvvsLOnTtRUVGBjh074rjjjsNpp52G3//+97b3e9GiRXj77bexbNkyfPXVV9iyZQt2796Nli1b4uijj8Z5552Hq6++GpWVlabaLS8vx/Lly3H//ffj7bffxoYNG3TTZqu54oorMHHiRMiyjF/+8pdpMU6EEBJEKHa8QZAzJ1sghBBCPGbz5s2pSU6feeYZDB8+3OsuEUKIJXbt2oWqqip8OuwcNC8z5467uyGKHi/8A7W1tWjRooVDPQw3oY96ikajWLp0KW666Sb06tULLVu2RGlpKdq1a4eBAwdiwYIFXneREEJIBi+++CIkSULTpk1xwQUXeN0dQggpGLeysa1duxZPPPEEhg4dimOOOQYlJSUQBCEVe2mVJUuWYMCAAWjTpg2aNGmC7t2747bbbkvFrPqV0LuxLV++PDWfRbt27dC3b19UVlbi888/x/z58zF//nwMHz4cTz/9NASBpkJCCPGa+vp6PPXUUwCAIUOG8G0mIYSY4KmnnsKkSZNsbfMvf/kLbrjhBgiCgFNPPRVt27bFv/71LzzwwAOYPXs2VqxYkcq+6TdCb9kRRRGDBw/Gu+++iy1btuAf//gHZs6ciU8++QQzZsxAJBLBs88+i7/97W9ed5UQQoqerVu3YsSIEfj+++8hiiLGjh3rdZcIIcQW3Eo93aNHD9x44414+eWX8cUXX+CSSy4pqN9r1qzB2LFjEYlEsGDBAixfvhyzZs3CunXr0L9/f6xduxYjRowoaBtOEnrLTnV1NaqrqzXX/fGPf8TixYsxbdo0vPjii7j00ktd7h0hhBAAuOuuu3D33XenfTd27Fh0797dox4RQojNCEJiMVvHJMpcZQpigXP1PPjgg5BlGcOGDcNZZ52V+r5p06aYNm0aDjvsMMyePRtffvmlL+/Zobfs5KNnz54AgJqaGo97QgghpKysDN27d8df/vKXtNTThBASdATBQsyOxyEWDQ0Nqfj2IUOGZK0/5JBD0KdPHwDAnDlzXO2bUYpe7Hz99dcAgPbt23vcE0IIKV7uuusuyLKM+vp6fPHFFxg9enTBbyMJIcRPuOXGZidfffUV9u3bB6BxkuhMlO/XrFnjWr/MEHo3tlxs3boV06dPBwAMHjzY284QQgghhJDQEsR5dtavXw8AaNmyJZo3b65ZplOnTmll/UbRip1YLIaLL74YtbW1OOaYY9Jm9VYjSRK+++47lJaWppkSy8vLUV5e7lZ3CSGEEEKIDrIsY/fu3Tj44INDaRXetWtX2me3xqG7d+8GgJwTSjdr1gxAdh/9QtGKnREjRmDp0qU44IAD8Prrr6OsrEyz3ObNm3H44Ye73DtCCCGEEGKWmpoadOzY0etuaGLFLU0pr1hPFO68807cdddddnUt1BSl2Bk1ahSmTZuGVq1aYfHixTjyyCN1yyomuzWP3YTmTZIKWpZRVlKC8tKiPHyALHndg2AiyV73INjYbcoXNB44eoGgWg8nrfpafdRrU+t79XYy16u3J+iU0/teo31Za32ubWagWV+pJutc63r3Dr3yJsnarpTjXmVkm0budXa0Y9d2gNz7bIZCz4lN5zQQ8N6eHxfGDbv316Hr1ffoulr5AUE075am3IZramrS5hxzy7tIOZ579+7VLaNMKurXOdGKbrQ+duxYTJ48GS1btsTbb7+dysamh+K6dnDrKrRoWpH4sphu4lpQ7FiDD8TCCKLY0RMLZoWOui29crmETkb/tYWOmPtzrroaaAqeXPcOG+4rtoodo/3J104+8WHXdoxsyygFC50iekbwvp4bD64Fr7OX5aKQmJ0WLVp4Iia6dOkCANi5cyd2796tKSaVjMZKWb8RPqfGHNx888147LHHUFVVhbfffls3q0RefPxDIoT4BKtCx0xbRtrPsOZYFTq6dXUwtB2vsOuFlZ+Ejl1Q6BiHQkcfWSqua8Eoomht8ZBu3bqhadOmAIAPPvhAs4zy/fHHH+9av8zgkyeP84wfPx5//vOfUVVVhcWLF6NXr15ed4kQYhSPs9HYhhGhk0tQGLHq6JTXFR8GhY4uZl3ddEWgzY8ju6wcTmG30LFjfyl0jEOhow1FTk4EQbC0eElZWRnOPvtsAMArr7yStX7Dhg1YuXIlAOB3v/udq30zSlGIndtvvx0TJ05Ey5YtKXQIId5gVehYteoYEToGvtMVOmqhZFaouCV4rGJHDI2b4oNCx10odLKhyAk8U6ZMQffu3XHppZdmrRs/fjwEQcALL7yAt956K/X9vn37cMUVVyAej2Pw4MHo3r27m102TOhjdubNm4f7778fANC1a1dMnTpVs1ybNm3wyCOPuNk1QogRgmLVydVPO97MmbXqJMkSKyaEhmnLjMZgRxYE/YQFJtrJW81PsZR2uK+5nZCgEDjILV547k1RSDY2M3z00Ue49tprU5/XrVsHAHjmmWfwj3/8I/X9nDlz0L59ewDAtm3bsHbtWrRr1y6rveOPPx6PPvoobrjhBgwYMAC//vWvcdBBB+Ff//oXtmzZgm7duuHpp5823U+3CL3Y2bFjR+r/Dz74QNff8JBDDqHYIc4iCnwjWCwYsVDYYdXRS0qQbNuQ0DFrzcnXH6OCJ5eoUW/H7sGUHaIoVxtBFDqFHJNiG+zyHt5IsZ17G3BrUtFdu3Zh1apVWd9v3LgRGzduTH2ur6833OaYMWNwzDHH4NFHH8X777+PvXv3onPnzrjllltwyy23+DsLniz76XWY/9i1axeqqqrww/T7mI1NgTc46/BBaQ6nrDp2JA/IbEPUsbbY4b5mJgObltAp1JqTq42sBvTvD6YztFlt28ksbIW4r1HoBB/ew3173nftq0PbS29FbW2t71IgK2PJ9bdchuYV2vM66rG7rgGHPvhXX+5XUAi9ZYcQ38CHpH+QJY3AfJfc5fKlmAaMCYt8gipXW4WKHEHQHySbdUMzU17pi1ODrULbpdAJN8V+Dy/Gc243Fiw7gXHl9jEUO8Q8Fn3qCfE1suy84DE6l46pOgbc13K0b9qSo5RX/moNmHVEien4HYMYbtPJiTILFTpuwmQE5qDI8boHoUEQRAgmE7GYLU+yodgxS7G7sBFCCs8aZkXoGCyr676WUceyyNH7Xk/0GBE8dr5AcSpg32mh45ZVh0LHHMUsdIrtXJPQQrFjBgodQogTGBE6uaw6JoSO6ck+jVq7cokeQ/U9thhb3XaQUkxT6JijWIVOsZ1nNxEF825pdGMrGIodo1DopOP1wISQQvCTW4BZoaPTd0tCJ292tYzyepYm9SA8M57HqHVHp2wWGettS0yQc5sW6/opTodCxxzFKHSK7Rx7gFupp0k6FDuEEFIoRt68GXlgaZXJ5z6WJYwMCB2zlpx8fVfWKwNypwWP3eTanpPua0EQOsU4AC42oVOM59gj3Eo9TdKh2CGEEDPYGa+jl15aq2yObedzTcsrdPQEldk3iqJoamCeU/AAeQdhjk8kSqFT2LaDSDEJnWI8v14jCOafIW5lCg0xFDuEuEExPUBJI4U8pHIJnXxWHSNCxy6Bo4cB607+NjLq5Kpv1YXNyoCPQid8FNM9utjOrY+gZccb6AhIrOOnuAdCjBKE69ZEbI1uVrXMdbmEjig2LoWSqw0zqa/zYItVx4r7mlsppil03KNYhI4sFd+5JQS07BBCiL0YjYfRc2HLJ3QMWnXyCp0cosSKADEsPszE79iBlXYt1bExxbRXQqfYBsLFJHKIP7DyUokJCgqGYocQpymWByqxHz2hkyQlSvSEjp41J+PhadW6ktlGSrAosTuZrmxG66e+NOjCZgU73dfsnkunECh0jFEM9+ViO6cBQBAECCbvt2bLk2wodkhhMAU1cRJJDsccA7kypulZdXIJHbNv+nSsOTlFjhF3P0MThmoIngLvG1nb0BUhNlp13LK2FLIdCp38UOQQLxEsWHaC4Hrtcyh2CCGkENwQYxpCx7BVx6jQsfJAzSVaTGZmcxW9PjsVp+O00GF8jjHCLnSK6VwGFCYo8AaKHUKcJOwP16DhtzdkRqw6uYROPjSEji0iJ7O+apBl2J3NTOyOqpxhq45ZgpqQgELHGGG9FxfTOQwDgmgh9bTPnlsBhGKHEEL8Sj6hYyRWJ5dAEjKtPcYfqoJ6kGXELc1E/E6iMw65jdk1OPRDQgIKnfxQ5BBS9FDsEOIUYX3IEvvJN+mnFaEjCLnrJTEjcDLr6QkeTeuOH7DLfY1CJxiE9R5cLOcvjIiCeddnurEVDMUOIcTfuJWkwG8Zb6z0JzNOBzrWHmiInMztWRlM6wke9TZyTDSaz4XNMKYsSBQ6oYMih/gUQRAhmHzBZLY8yYZihxQOM7JlE9aHbZBx+4GRFRujMZFn5veFWnXU7aXFAynlNNrXE1V636sG2kp7Qr7fv1nrjk57BcXrmLlHuZF5zQuhUwyE7d7LZ2u4oGXHEyh2CCHFgSxZEzySZO+kbnp9yDHxp61xOur2VeRyZ0t3V0vWzRA9eQWPWxRq1XEj85pXQscv58gJKHJIABBEEYLJ54nZ8iQbih1C7CZsD10/4IYrmyz7w5WtkLlvtOJ0Mq06aS5uxh6imhacDNGTEjz5XNnMkGvApyUYzCQlCJLQoTVHn7Ddbylywo0gmH/O+OG5FHAodgghxI/ozaej+l8/Hie30Mkbr5PWWB63NaNZ1nKloYbKRc2oC5tRjAods21YadNLoRPGQXSYhE4Yzw8hPoFihxASDNxKVOAlGaLDSLrotLq54nQyhU6u+XbMuq0lBYyWdccyZusbFQVOJCTws9AJ4yCaIocEFVEw7xYd9ueeC1DsEGInYXoIE22sxv7kIrO9zIdhRpwOkGG90cq+hjxCJ9c+ZK6TJU23NSB/coKCXdm0MCocjA4knRY6VqDQ0SYs99gwnhuSH7qxeQLFDiEkOPjdumOjCMqeN0dH6ChkWHU0hY5GPb0kBmkCRSmvIXpMkceVzVbsiNOxC7PboNDJhiKHhAAmKPAGih1SOLx5JwjLw5i4h5bQyPNgyzt5qEZWNy2ho5nhTfVbVq9PCR+1e1qW65oFV7bk+qx4nYx6eS1DRsRBUBISMBlBNmG4t/I5SYCkJd6keOE8OwVDsUMICRaFWHeccEGzi1wTgeolJMjlvpZP6GjOuaPxnSylu6JpCKN82OrKlike7JqI1Gx9Ch3nCbrIocAhmQgW5tmhG1vB+PSpT0jACPpDOWgE/Xjb4ZaQY/JQhUyhIwtCmtCRIegumW2m6qq/10l6IGeItCxUg3rbs7AV6r4WBqET9EG2JAf7Ny5LwT8HhIQIWnZIYfCGTkgjWpYjq8LG4uShisBJSy+dFDpp7SH320JlvQDZlrlzDNczM7eO3e5rXggdWnMaCbLAAfg8JHkRBBGCSe8Cs+VJNhQ7hBRK0B/QQcXvyQqMYuZBphenk1yXZslRyukInXwTiipZ1mQIjYIH0HBry5NswI401EbJ3I7bQscPbmtBHXAH+T4a1GNO3Ee04MYWhuecx1DsEOvwBk+CSK64HVk27x9tp+gSRc3EAXKmgEmSJXRS34vZ6aUFMWWtyetmBkAZegqypGvlSbf46CQqSLWTMZhV3z+MuLDls+oYETqFQKHjDEEVOUE81sR7mKDAEyh2CCHBJSzWnUxMpplu/D/bYqPE6KRZc/KknhbkRlGjnk8nZeWByi1NEAFIxt27tOJ13MKqVYdCx34ockgxwnl2PIFih1iDN/wEQX1ghwkrgsdsVjZJsiepQKFoua8Bud3XVBadxLr0+trubJJKyCAlegQNi46aTGtO5ufGFTpWHb37ih1WHT8IHcbnBPeeyWcesQNRNP8s8cOzJ+DwCBJCgo+dA6hCg+gzUQ+G9QSW1ps7Qcd6A2Pua5kWGznpPqFkVZPVMT7qJVk2LfuaehvQdqPLEltIxv3IkirjmnGrju56Ch2NtgMyEA+i0GFmNUICDy07xDy88ScI4oObNOL0nDtW4n9yobLqJD7ndl9TyqTc11ICRmuOnsa6ApTEBMp3jVYeGchr3dFFEQZ6dYxadcwSdqETBIJ2r+QzjjgFY3Y8oSiO4Nq1a/HEE09g6NChOOaYY1BSUgJBEHDfffd53bVgwTdcxM8EbUClIYSyrTHZk3+adV+TVQ9XtSVHsezISjllybD4KFYe9TY1rTvqPhWIbVadQjKv5YJCxxhBmy+HzzjiNEo2NrMLKYiisOw89dRTmDRpktfdCDZ8AKQTpAd4MeFkwgKn43Zyta1h1cnpvpaZkADZIildsKjaVltukLD0JKw8EgSosq9BSMz/oL435EpDbSUxQS5RYTX7WqEppil08hO0+yOfb8QtNF5gGapDCqIoLDs9evTAjTfeiJdffhlffPEFLrnkEq+7FBz4posEDTMDLV2XKn8O1rIyp+m5r6WVUbmvKZYalQVHFiNpMTtqa49+e9ouc2kf1fE6ei5sZu4t6nNiNU6HQsdZaMkhJDeZMZJGF1IQRWHZufLKK9M+i8xsYQw+BLQJ0sPcIWQL14ars0CbsfA4Hbtjdluq+JoUWlYdg+5rekInLWZH9d5LEFQxO8n+pll3DCVwMPkb0ZqPp5BYHat1gyh0/HCfDto90Q/HjBQnzMbmCUUhdogF+DAgSawIGyPtOC5+CnVpy5dgQC1c1NuyUzypRIl2/E4O97U8QkdGdsY2AJARgSDLEARJX/BASVYQz+6y0evFKauOEwkJKHS0ocghhAQAih2SDh8GuQnaw70A7BI5Rtp3TPgYFTxGBYoP5ttRixczZbWEjn4bEiCLKcGjJWqAxrgdWbH4ZAz001zY1N/poGnVodDJ2IYP7tFBug/64XgRosBJRT2BYock4AOBwHmBY2S7tgsfJ5MWFEqh+5rHqgMgp9DJFZeTcFlLfJQhpKw7MDrOlXUES65yZnBa6FDkZBMUkeOHY0WIFkw97QkUOwbZvb8u7XN5aQnKSwN++PhAIEm8EjlaOCJ8jAgeLeuOnXPl2NBWmlXHqPtaDqGjWHbU7mwJC03iWMgZ7mxCsg96lp7GNvIkB9BYb9qqo4ZCx1kocgixB8FCzA7FTsEEfLTuHl2vvT/t823/czpuP/8Mj3pTAHwYWCcoD3wT+EnkaKH0zxbRY1XwZLWjcmUrND7HSH2xUdCkkaNelqubjtCRk2Iova6QSFcgS4ntJt3ZIDcKHVkQ0tJQp/YFyDn4z3JhsxrfYyhJgsNCx63YHC9/o0G55/n8PkZICrqxeQLFjkG+efI2NG9SkfocCKsOHwBEB7+LnExsEz1WBI9Ri0yutg3E+mglC8i3XV33tUxRk0PopM3FAwECZMiQAYiQAIiIp9zZUn1S3NsMWHmMkNeqk7bTBtzXnBQ6xZCAgCKHEGegG5snBGDE7g+aN6lAi6YV+Qt6BW/6zhKUh38egiZyMrFF9LgRw6MIpkJc1zTnsslIG63jvpYVp6MjdCQhkt7t5CShiRgdQEhac2RZTn6Q0uxAhjOvmUXPfa2YhI4XBOU+F/D7GCHEXSh2jKJMPlaoywpgrQ3e3EmBBF3oqCk4rief4Mln3bHTlU2N1hw7ShfU29AoI2cIofQ4nYTQkcSIytqjnaRATgogUY43ih9BSNp8xITVR5CNpZ2WpMSxk1Xz86Tc3ZLCNde8OlbidPQIitsa4P79PggiJ0T3L1LE0I0NAPDuu+/a1tavfvWrvGUodsyidcNNGxQZeTvIm3agCMJAIA9hEjqZWLb2mLXwGLHSmG3TaJ/ThI56MtBGq46yLiVg1HE6GgInM0mB0p7ixiar3NlkyIlkBTDosiYbnHxUs65B9zWd7Zqq6zehQ5GTTojvW6RI4aSiAIB+/fpBsEHECYKAWCyWtxzFjh3whhxe/D4YyEOYRU4mlkRPLnGSz2Jjx5w7+bYhpltwMq07jd9nu6+lxekIGjE7STe2LAtRhqVHRByynHCFEzJ+DkrMjq6wUTK7ae03NKw6Triv+VnoePH7DMI9rYjuW6S4kJNuxWbrhJGDDjoI3bt3t1z/yy+/xI8//miobFGInY8++gjXXntt6vO6desAAM888wz+8Y9/pL6fM2cO2rdv73r/CHGCYhI6akyLHmXwpyV6jCYr0ExbnSNuRxFKZh5iaaJH7aomaruvJcWNImhkCCqBo4geISFkkJnpTfWvpjVbW/xk7WMmVrKveSV0KHLcpUjvV6TI0MqsaaROCDnrrLPw/PPPW64/bNgwvPjii4bKFoXY2bVrF1atWpX1/caNG7Fx48bU5/r6eje7RfyO3wcHOShWoaPGkugxInjS6mhYd3Jai2QA5mN8tCw6igUmc/LQzDgddTKCdOuPAEmOaE4smhBAKvc3QYnVSYgjzb2TZUCWNcVRTpc2LauOuk2tsmllKHRy4vf7GO9VpJhgNjZPKAqx069fv0Q2IUKM4vcBQg4odNIxJXqMCB4z1p20tnO4vRl1h1NlYVP+Zk0eCmTF6ShCRxIS4kaCCFkWGwWNhnwRBDkhmuR0C5Be3E5K5CjxOkZc2PK5r6kpVOh4LXIAdwf2fr+H8T5FSNHy6quv4tBDDy2ojWuuuQZnnnmmobJFIXYIKRYodPSRZck+wZNW3obYHS0yhY3SDbW7Wuq7xgQFaRaczFgeRehATP5Nih05fX8FQYYkRxLJCgQxa30WKQEjpYsYjTKJcnoxPjrua0EXOm79LilwCPE1jNlJ8Mc//rHgNk466SScdNJJhspS7BCSid8HDBpQ5BjDsJUnn+DJZ91R6hudb0eSgIhqzhuVhSbVtMr9Ic2FLc2Kk+GmlrTkKNYdLaEjyenppwXIiMuRxDw7ECGqXdlU/REUlzVZSS+tbckR9Kw2ZtzXstbbKHQocpyF9yZCGqEbmydQ7BAScCh0zGNI9ORKXJBopFHAOGXdUVALpQwXNrVVJyvNtCJylCQFcqPQkTLc2BTrjSCov41AEiSIqjl1ZEEEpMZUn4ZSTJux6uSL0zEqdLyw5jAeJwHvSYRow3l2PIFihxA1fh08EEcwLHrUgidf/I6edQfItuBo9UlpL1M8qdwfUlaWtOQEorb7WvKzJEfShE7KuiMLkFRxOxFZAgRAkkWIgqTappAmrICEFQhQ3NcyXNAyB7y5rDpG43TsEjpBFjl+vUdR4BCvCYIFhPPspFFbW4sVK1agvLwcvXv3RrNmzVLrFi5ciDlz5uDHH3/EkUceiWHDhuHoo4+2tB2KHUIU/DqIyEHorTqZ58TMhJ0myCt6cgmeVBmD1h1ZTkvtnLd4ZswOhLTvUxnYUladRmtOyo1NlV1NLXTispi2HkDCfS3ZRymZoEASIojIMVUSApWYybwGpQwrjp5VR0vo5IrT0Ux24LHbGkUORQ7xjiCImwwYs9PIzJkzceWVV2Lfvn0AgLZt2+L111/HKaecgptvvhmPPvpoWnKxyZMn44UXXsCQIUNMb4tihxDAvwOJHARW6BRyrPPVLVAM5RQ9eoJHy51Nc94dVTlZAjLntsnVr0w/71RMj5ht1VG7piUTEkhIWHUyhY6kIXZkWYCQnEBHhDJPT6MbW7oFRxWvA4OJB/TECIVONn69LwX13kOCSwCFDdHn008/xSWXXIJYLIbDDjsMJSUl+Oqrr3D++efj1VdfxSOPPILjjjsOF110ESorK7FkyRL8/e9/x5VXXolTTjkFXbp0MbU9Xj2E+HVAkYNACR1JTl/c3JbFbeoe38y29OJMMstrtWckpiTzAa9OFJC05GRadTLd12RkCyBF6KiXuCwgLguIyWJK/EgZyQzUYiaVeU3rWGSug06qaa3jZ0XoSFLu46kSZAWRSsjg4O/Prd+KWdzYd0KUFzuZS1jQ2798S8h4/PHHEYvF8Mgjj+Cbb77Bl19+iaeffhpbtmzBFVdcgd69e+P999/H2LFjMWLECLz++uu45557UFdXh6efftr09sJ3BJ0i3yDKrw8okpsAnq9ACB2//R4siB9ZlrSPdT7BkxrQS9rl1YNyIwNwDRcGWW3ZyWXVScbpqK06aqGTED6JJVP8SCrR0yiihETLaa5pOaw2WoPjfHE6mfWzvnM5PsetQb6ffi9qKHCIk4R8UJ9J+sso40vYWL58Obp06YIbbrgh9d3w4cPRtWtXfPvtt7jzzjtRUpLufDZ27Fi0atUKS5YsMb298B1BP6AnjIwuxB0CeKx9L3SCcg2b+L1pip589Yy4aplBZb1Ru7Al/mrH6mSml84UOoo1R/05JiUXWURciiAmRxKCJ3MeHllOJSdIfM625GSWN+2+VqjQKcSa47bA8dtvhlYcYjdFYrHIi5JYxuwSMjZt2oRjjjkm6/sePXoAAI4//visdU2aNMGxxx6LdevWmd5eEV5pNuPEQ4rix3kCeFx9K3SCfq0a7L+m4Ml0U8scXGfGtzQ2pv29gk4Qq7YLm3puHVX2NVWcjpbrWlwWEJciqf9jUuO6qBRBVGqcowdAqn3N/dNyYTNi1XFS6FjBrQG+H38vFDjETopd1OiQnjXT4BLCobogCGjatGnW91VVVQCAAw88ULNe+/btsXfvXtPbC98R9AK34xCIdXgM7SVsxzLP7yynlSeXO5tWewYGlSkXhowBQ1piAq0JRGXV/yrBk2nRUbuwKf/HZQGSlPiblqUts+96+5tByqpjJk4na3sGhY5Va46bcTh++c2oxQ0FDrEKLTa+57XXXkO/fv3QqlUrVFZW4thjj8XDDz+MaDRquq29e/fiwQcfxIknnogWLVqgtLQU7dq1wznnnIN58+YZbqdNmzbYunVr1veyLKdlYMukrq4OLVu2NN1vXpFBJF/MkJdLvn56iV/6YQHfWXX8dF6dIo/oySoL5BYAkmLtMDHIV28z6cKmWHFSrm0ZVp3UXDpQWXGQ7bqm/FVc1yRJQFwSEU9+Vqw7MTkCCRGIchyiFE/NqSMkhUWmC5uuVUePfAkJMo+XnS6CbokcP0FxQwqBoqYwXHZjGz16NP7whz/gvffew0knnYQzzzwT33//PcaNG4fq6mrs37/fcFvbt2/HSSedhFtvvRVr167FySefjN///vfo0KEDFixYgPPOOw+jRo0y1FaXLl2wdu3arO+feuop/Pzzz7r11q5di3bt2hnuswKv1KDjt4epEeHjVp/9+DbVAr4UOsWEzjWUZeXJ5dKWYy4apWyumJc0lzZlkk+oXNaSVh0pae1JzY8DEZKORSf1VxIgJd3Y4pKQWOSE8IlKEcSkkkQmNsgQ5DgEKZ7aJyHTwpOxn4asOmk7mkfoaNaxYM1xcsDvx3sOLTjELLTYOIMgWMjGZk3szJ07F5MmTUKzZs2watUqLFq0CLNnz8bXX3+NY445BitWrMCECRMMt3fPPffg888/xwknnIANGzZg0aJFmDlzJj788EMsWLAAJSUlmDx5Mv7zn//kbatnz5744Ycf8NVXX6V936RJk5QrWyYbN27EF198gRNPPNFwnxV45RLvKCRJg1krU0DxldAJ6nHNdNcpxH1HR/SkrVe2mfpOY32iYvpfLVRv9VKppIVskSMLyflwkgJHsezENZIRqC06cSkZrxNPpp2WlCUhfNRxOzIEiHI8LTlBSvgk9zHLqqMVh2M0Tseo0DGDUwN+P953KHCIGShqXEFOWeTNLVZ44IEHAADjx49PC/hv06YNnnzySQDAlClTUFtba6i9ZcuWAQDGjRuH1q1bp60bMGAAfvOb3wAA/v3vf+dt6+qrr8azzz6LiooKQ9sGgNmzZ6Nz584444wzDNdR4KSixJ/4adDgEb4TOn7EjmOk10auB75yPERlIs7kYF8QE+tEAamJQwUhMVgXk20q36e2rbMdZfuqwUe6C1um4FGlmtZJRqAWOpLcaMWRZSAuKfuS6LIsAiVSY9yOLIiNlhyVO56QabVRup9PzLkpdJwSOH7DT/cM4k8oZLzFipi0cM42bdqE1atXAwCGDBmStb5v377o1KkTampqsHDhQlx44YV52zQqTNq0aZO3zFFHHYWjjjrKUHsKo0aNMuwmlwmvekJIbvwyqCvUKlPo9rTIeJufEqhqC09WcL1GPE8mosatOenOkLLiQEiz6qQJHaTH6WRadNRCR5ISlh1JZdmRktYeZR4eJcGBOkZHkOLZ1ho9i1Yu9zWzQseo25oT1wktOCRI0A3Nd2TOhWZ0McuaNWsAAK1bt8ahhx6qWUZxB1PK5uOss84CAEycOBE7duxIW7dw4UL885//RLt27TBw4EDT/XUaWnYI8SG+sOr4ZUDnh2MBZPdDPXBQrDlInDtNC0+mdUeIJAbtkpS0/giAGEnfpGLRUU3smRI8YvqcOnoTh6rn0lELnVgyPkeShcT4XQKk5Hw6cQmIiMq4XlS5sEkJFzYNUaO28Jiy6qTtsAGhYwS7rxm//BYU/PKbIP6BQiZ1DybA+vXrAQCdO3fWLdOpU6e0svkYN24c3n//fSxatAiHHHII+vTpg5YtW+Kbb77Bhx9+iD59+mDatGm6MTdeQrFjFFFILIU89DJ/iH57gBLP8YXIAby/Nv1yHHKh9FEZZKhc2/IKHkkEBGPHOC1OB0JjumklAxtUc+okhU5cjqTc1uJypDHjmobQiUsJFzbFYKLsRkQE5GQq6jKhASVSNBWTI6SyssmaiQlyWnX03NfsEDp2XTdeX/96BOF3QZyHwiZBAMVNajoBk3UAYNeuXWnfl5eXo7y8XLPO7t27AQCVlZW67TZr1kyzXT0qKysxf/583HrrrXj00UexaNGi1LoDDjgAp512Gjp06GCoLbfhL8YsiuhRL0bK6JUjJIkvhI7XLjoeuOPIkmR4MdTn5PFLZWvTO56ylMxUpuHqBmQ/EFVxOinXtUyrTmacTlLoJKw76UInJgmIxYFYXP23cdlbJ2JvQ8JdrhQNKIvuTbfa6ByHvFYddfnU/wUKHbuuG6+vfz3oplZ85MrOFQb0xklmliBiOhNb4znv1KkTqqqqUsuDDz7oate3bNmCPn364IknnsB9992Hb7/9Fnv27MH777+PE044AXfffTf69u2bElpmueWWW2zucSO07NhBIT86pa4fH7DEFXwjcrzCxf3XFSwW6wvq2Bq1pSfTyiOJgJhh3UEkPf4kZSFRubKp0pQqLmwJkSM2/pUjaXE6jQInkpokNJ7MrhaTGjOvSUmLTlxCco6ddMsOAOyrExFpLicTEyT/SvHGvma6sOkeOANxSnrrzYgmq/jp/uuH+wExhqDx+9daV4wEVYw4jJXsakr5mpoatGjRIvW9nlUHAJo3bw4gMQmoHnv27AGAtDZzcdlll2H16tV4+OGHcdNNN6W+79WrF/7xj3/ghBNOwMcff4xHHnkEd999t6E2FcaOHYvHH3/cMQFX5L9GHxGWtxY+QXmrbtfiZD89xcs32S68rTZkmbG7/bTUy41WHqgnFZVUnwF9EZCaMFRodGFTEhQkhU486cIWU7muKZYdJb10LJ4udDKtOLF4Ik4nGgNiqqW0pPHaSLitxVX/a2dhy5llTev7XEIol9Ap9PrxW7IBWm/8g4m37bp1wk4YrS4u0Dh1gLkFSIgS9ZJL7HTp0gVAQiDpoaxTyuZi06ZNWLx4MQBoZm4rLS3F//zP/wAAlixZkrc9NaNGjcLjjz+OwYMHm6pnBlp2/IzVG4ZfHt4u4pRoEBx8aPlC6HiBC/ttm7DJNweOznYFUVQJGTHbwiNEGq04kpRITJDjuCgPPEmMqNzYsl3XYrKIuBRBTBYRjUdSWdUSogeNsTpSwm0tEa8DxJPGmoR1J7HPJREB5aWJ/2NCKeKRMpRE9yesO5nHx4gLWy4xY0XoWMVP90ev7wEkQTGIE6tQuNiLau40U3VM0rNnTwDA9u3bsX79es2MbB988AEApM3Bo8f333+f+l/PEqQkJsjM1JaL66+/Hk899RROPfVUvPTSS4brmYW/8DBihy9sgN7YWBUNgiDmXUKH12+znbSS2WHBSQXcG0hvnFlWVSfL0pM85ikLjxRXWXcaLTyCLDcKBtVkosoDUoaQitWJyyWpeJ2UVScpdJRkBA1xMZmcQEBUZcVp/Ju04sSBWFyGJMkpq44ihGKSiAjiEKWYKtlA4zE27MKW+ixpf5+rjlZ9s/jBimMknTmxHzMWmmIjCM97w7EtPumvD+jYsSN69eoFAHjllVey1q9YsQI1NTUoLy/HgAED8ranTjywatUqzTL/+c9/AEA31XUmI0aMwJNPPomjjz4ab7zxBsrKygzVs0KR/8qJJfRuiB7dGI2IFr8JGdesOmpx43VcjgP7XLDAMSpuJCn/ktmmqn+p/VcLHkXkKK5tinubunvJmJ1UQoJkumnFdS0uRxJCR06KnKTQicbFhNCJZyYiSHdbSwidRpHTEAViMRkNURl790nYsSvRVonUgJLovsb9U45JrnNq9Hxnnju7hY7X1z5xh7CKGSNCJEQvL0N3/jKx4sJm8RjceuutAICHHnoIH330Uer77du349prrwWQsKyoU0XPmTMH3bt3R//+/dPa6ty5c0o8jRo1Ct99913a+pdeegkzZ84EoD2JaSZXXHEFnn32WXTo0AFvvvmm4+mq6cZG7EEteDiw8BY/HX+HRF3Bbmr5rBFW2s+so0pe0OjeBkASIYsSBFlIzK0jiI2CKX2anURdISPNtBCBhEij0JEaU0srQieWEaeT6bamWG4kSUY8KXxkSU59p+zKjp1xHN4OiEix1HETLAmODIuQ0fly0g6ERaHjJ/INWoJq7cncr8y07Lkws89hGfjaJTK8Eita50F9HsNynhzAyiShViYVBYBBgwZh5MiRmDx5Mnr37o3+/fujsrISS5cuxc6dO9GnTx/ce++9aXVqa2uxdu1a1NXVZbX3/PPP4ze/+Q2++OILHHXUUejduzfatGmDL774Ap999hkA4OKLL8ZFF12Ut28vvPACWrRogTfffBMdO3a0tH9moNgh9qN1A/bboMNDbLHq+P14+lHk2CVwjA7U1e0lhY8sSSnBk5hnJ55YJ8UBWcnOlj5okAURsmLREUtTVp1Gy46IqBRBVIokkhEkhY7ithZPCh0pTeg0ihwpLifjdmTEJTlpaEoInqZNIzigyW5U7v4x6WLX6G5nKC7H7DG3IoJ02/b5byRomBnAOlXW7/jRUmKUQs9DmM6jgxQyz44VJk2ahD59+mDq1KlYuXIlotEoDj/8cIwfPx5jxowx5TrWo0cPfPrpp/jLX/6CN998E6tXr0Z9fT1atWqF3/72t7j88svxhz/8wXB7+/fvx5YtW9CjRw8ru2YKQZbtfLqEj127dqGqqgo/PH83WjStCO+bOa8osgEJhY7VJj0UOXbcIhVfcjHhVy6ICdcEIRIBIhGgpBQoKwNKyyCXVUAuq0C8tAJSSTnipRWIRSrQUFKBaKQCUZQhKpeiQS5FNF6KBqkE0XhC8DTERURjjRadTJe1TGtOPC4jHk8IG+X/hOCRIctAy5alOPe4LehQ+zmEeDQxmWhySWQ1kFITjUKWICiZDoBG9zzlGBvJwJZrDh8z+P03kgu9fbUy4LH6W+TANZugCpmgn0sTcTi79u1H2wtvQm1treF0ym6hjCXXrVqK5snJPI2ye88eHP7L/r7cL6s8+OCDuO2229CiRQu88847OO644xzdHi07RjHqN6mUMfqQUbdZjELJyAMkyAMXJ9A7Zl4fJ79ZcxwUOWb7lJqPJx5PJBqQ5URCtjggiELi2MXjQEm6ZUedhU2J1YkjgqhcgphUgmjShU0tdKI6sTla1pxYTIYky5DiMqKxxF9JSvwtLRNx8EECyoT6dPczrfOcOdmouoxhQUOhAyDxTLDLJUivrhk3s6BgxKNAz806aEImiOeNyQMAIDF9gMlwebPlg8Att9yCkpISjBs3DmeffTZWrlyJQw45xLHtUew4RT7RU+wixwyFPIiCPvAxgxfC0YV5csxXckbk6PbFwDGVpXjq/AhiIkZHRjIDdTyeSJgRSaShFmQZqRaVxATKkozVUSYOTYicbKHTEBNSmdYUUaPlsiYp1hzFwhOXEZckxOOJHrRoIqEitjfncbGeHc2Baycsv3enB7NBGCzbIUC02nBD2ATh+BqFIoU4xE033YSSkhKMHTsWZ555Jt577z20bt3akW1R7DhNpugJ000wCJh5sLkwUBIE0dv5dYy+/dT6PhM/ivR8GdUs1NUUORrHJu95jSfPf1L4KKJGABL3hXhclZJaSliABAGyEIEkiIiLJYjLCatOVIqk3NfUQqchJiTc2OKNmdbi8UaxY0TkxOMSpJiESERAVZN6NNvzQ3Z6aSNCxQsPaSZI8S9Bs56oCepzOyxCRbGMS1Ja4hfdcj5GTt7XzdYJK2PGjEEkEsHo0aMxcOBArFixwpHtUOwUSuYAR++mmM+dgHiHy4MjJe2155OKKlgdhGS62wQZjYG5EZGTdQ7zXEsykhaeeKKsoGxHECHEoonYndQ8O40ubHGxFDG5FLGk+1pMKkE0HknE6sQE1MdExOJANCYk0kcnBU4snhA4CbGj7a6mFjmyJCMWlSDLMtq3a4IycU9a/y1lYiuEsFxffiTI4qMQgipcgOCKF7tESADETD7cTlAQBEaOHImSkhKMHDnSsW1Q7BSCju86APtTbhL78MmbX8+tPHZgNkbNdPNi4WmmAXtcpnIJHWWdxnGQM+oJsjJZaGLOHSESAWLRhLVHse4o8/SIEcTFEsTEUsSlCBqkUjTES1CfFDr1scQSjQmIKvPkxGU0RJESNrF4usiJx1UWHJXIicdlyHLjZ0EUUFHSACHpVCfIEmRBTBM8eScUbTwIedbb+JtUrDtBzQqp7rfSXzMW2aAR8oFcGkEVK5n4TXQoxzUAx9fN1NNB4tprr0Vpaalj7VPsWMHIwI5ua/7Cp4OcUAgeIPd17tb+6Q2YHYgNySd0UgJHY9uNxZS004olR4BQEk3VkYXEnDpxoQQxJftaMsV0QyyCumhC6DREBTTEgGgUaIjKjVadmIxYTEqJnFhUynJVyxQ4spRIWKD8fwB+svnImcSq9VBv4G9WEOS6b7ghLnJtw4/iJsjPuwAMlA3jNzGiR5iOuUFo2dHnqquucqxtih2zmH3waomeMAxug4BPBU4moRE8ehRo/bHNulMIqmspl9DJFDlpmf219iEeT0vLLJeWJtzZZCkRqyOWICYmUk1HpVLUx0tRF4ukLDoNUQH10YRFJxqVE2InKXQaolJK5ERj8eT/8UaXNVmGFJMaxY2ccG1T2LsvjrJ4XSqtdBpiMsbILgTBmxiffPhRUBihSAZHmoRpAE3REjoYs+MNFDtG0Xrgm61PnCUg4kYLoYDBSWCEkkXRU5DQsRhIb4e4SgkdSWoUQbLq/yRCPA5ERYiSDCESgVDRNFFULEE0Uo4oylAvlWF/rBT7oyWoi0awv0FEXYOA+gYgGpNRX59wU4tGE9achoaE0GmIxhGPS4hFJUhxKSl2FLc1KSVylP2VJBlicoB/UJtSlMSyZ9FO20dBSMyN6iT5ZmsvtE2nfz8UHsVLUMSKmmI/ZySUFJXYee211zB16lR8/PHHaGhoQNeuXXHRRRdhzJgxjvoKEocIsLgpBMfFjVPH1UK/DYsOLauAXULHglUnS+jIipuYlKqnbksQxEQKalGAWFkPAIiXlKEh0gT7pQrIQgWqKkvRpiSCshIBZREB5aVARJSTxgcBsRhQHxWwtw7YtVfAzl1x/LRTwNZtMmq2RrFjVwzxmAQpHk9zW0vsigQxOSiXRAGCKOD8jv9GaUMy7bQgQhZkCLKN1pxMzFh37BQQYRYjegNX9XEutsFt0ARIsZ0fM2T+dgPwW2bMjjcUjdgZPXo0Jk2ahJKSElRXV6NZs2ZYtmwZxo0bh/nz5+Ptt99GkyZNvO4mUShSIaOHK9YbJ4+5U9acQlyfCqmbx31N+V9L6MiyBDkWT32nCCNBECDH4hArKxP1WxyEVi3bo1PTJigtEZKblQEZEAQZgiAAaQ/BZOIDWYAkA7JcgoiIZDlgz744vvm+Dl+uq8Pn3+zD59/sRV2dSnCJAkRRRKQ0gggiEKWY9r4LImBW9GjF3iTnG0ovl/FQ96NrWyZBHIwGsc9A8ISKmqAecycJgDixG8bs6FNbW4snn3wSS5cuxebNm1FXp+1ZIAgC1q1bZ6rtohA7c+fOxaRJk9CsWTMsX74cxx9/PABg27ZtqK6uxooVKzBhwgQ88sgjHve0yKCgScMTdzQfCZxEFRN13JhTR8uqYyROR+W6piV0pFg8ESPTEEv8nywf21+Pkrbt0fS409C0qg1kWU6JFQAQBQH5XvIJgoCIRplmTSP4f0c2xTFHNEUkcgBicRlffL0H7/9fLVb93y5s2FKPktISlJaV4penHoJILPkwUYsbQUBqxlPlf7NJBNQWHC3Bk1mW+IMgCw0z8JpLp0gG2m5By4423377LX79619j8+bN6bGuGggWfqOWxc5bb72FM88802p1V3nggQcAAOPHj08JHQBo06YNnnzySZx66qmYMmUKJkyYgKqqKq+6GT4oZgwRGpFT4H7YZs1xUehkN53RtjpDm9zoOqYInXhDFFI0hlhdFNH9DZBiEg66axQizRP3ISs39VyIqoD7koiAXxzZDEcf2QxXXNARP26rx8o1e/DZ9wJO6rYfqEcy1XQ8EZuTFDeyIAKClP74FUTIkIw/kjMFTyZeJ6RQKJYBfhCgCLEHihdPkWHBsoPwn7ObbroJmzZtwimnnIKxY8fiiCOOQPPmzW1r37LYGTBgAI444ghce+21GDZsGFq0aGFbp+xk06ZNWL16NQBgyJAhWev79u2LTp06oaamBgsXLsSFF17odheDCYWMZTxLKOAzK05jVZusOQXUNxynkyis+te4+1rjOqnRCiTJkGJxxOpjqKutw85Ne9C9uXsvXNTi56A25Ti3ugyDIgLi0Sgafu6G6I6tkPfVaosYUUwcT6txPLlidCgy3Idiwp9QnIQKWna0WbZsGTp37owlS5agoqLC9vYt/4qOOuoofP3117jhhhvQoUMHXHPNNfj000/t7JstrFmzBgDQunVrHHrooZplTjzxxLSyRY0kG1uIKWRZSi2u4sY5s7hPsjLwtxML7eUSOsa+10gznbmNDKtOSgQl/1dc2RCPY/vy/5jeB7uIJP3fIqWlqDiwA1p074VmR52MsraHQiit0HwjWVBaVEHg4peFGEMQ3V0IKQLi8Th++ctfOiJ0gALEzmeffYZly5bhd7/7Herr6/HMM8/g2GOPxW9+8xvMnj0bkk/cENavXw8A6Ny5s26ZTp06pZUNLRQxruOJwAHcETiFpmN3GwtWoVznLjOFNADdWB1lnbquOlYHAARRRHnzMqy9eQy2vv5aQhTFdZIEuICSDl2saIryDkeg8tjfoOKIExFp1Q4QI8YaUT8HOHAjZjEy4Kf4CBeiaH0JwPlJzLMjmlzC/zKiR48e2LFjh2PtF5SgoF+/fujXrx82bdqEp59+Gs899xyWL1+Od999FwcffDBGjBiBq666CgcddJBd/TXN7t27AQCVSoYjDZo1awYA2LVrl347+9OzQpSXlqC8NGD5HUSBgsZFQumu5jW5XJ8sYJdlKVesTuKjIoAkTeuTIAooKY+goqocsiTjx+enom71Mhz4Pxeh6QknQ0kGIHjg3qWOGyqpOhClrdpCjtYj+uMGxH9YD3lPLSDIxoRvAAYjRUkh9yo3zimvG/9D11ND0I1Nm+uvvx7Dhg3Dp59+ih49etjevi1XZ4cOHXDvvffi+++/x8svv4zevXtj06ZNuOOOO9C5c2dccsklWLVqlR2b8oyu1z2ItpffmVr+PPefXnfJGqKQfyEF4+lEnzyH2RgVSBbm1Gkso5+BLReCKCTSPZeVoLx5RXIph/RDDX5+cTK2PTAS+xa/jvjW71OiSpYcnO8mZ18TjwyhtByl7buiyfG/Rflx/SG2PxwoKfNmwKN+s0usQUsHKcSiwt+eYRKWHfNL2BkyZAhGjRqF6upqPPPMM/j+++9tbd9W00RpaSkuvPBCnH/++bjjjjvw0EMPoaGhAS+//DJeeeUVnHLKKXjkkUfwy1/+0s7N5kTJ5rB3717dMnv27AGAnEkWvpl6C5o3afQlDJxVxwy5BsththrYhKdCR8FpK57ZdMNuYNJKYzpWJ0+qaVXDOtvLbl8QRYglEciSjFJRSJURSxLiRyyJQN6/F/XvL0Xsv+8h0rI1Sg87GpFOR0A8+DCIlS3S9sVNy4+yrUiLAxBpcQDkI05A/KcaSJu/hrRtEyDFGwdBWufGib6aadMuV+vMbfrEhZsEiFzXbeb1ZDR7IQWIL5FlAbJs0rJjsnxQGTFiBN566y1ce+21OcsJgoBYzJyLt60j9h9++AHPPvssnn32WWzevBkA0LNnT5xxxhl49dVX8d5776Fv376YPXs2Bg4caOemdenSpQsAoKamRreMsk4pq0XzJhVo0dSZwKlAQSGUF0EQi0PwFIggiubdyPQsNLna0aiTT+jkysCWXs768U3svwyxJJLVJ0EUIZYmxI7ajUzeuwvRrz5CfP0nQEkJhOYtETmwI4QD2kOsOhBCVRsITZtDUMXUyLKcPAbqvmr9jmVVkeQ/gpDWVu79iaCkbRegbZfUd7HvPkVs7SogomojFgViscQxFSNAWbl2g1IyJkxw4M2xljhVrBRmt0VxQ4xg5Ro2em1R2AQI0UIq6fCf308//RS//vWvsXPnzrzPVSvPXVvEzsqVKzFlyhT8/e9/RzQahSiK+P3vf49Ro0ahb9++AID7778fzzzzDEaOHIm77rrLNbHTs2dPAMD27duxfv16zYxsH3zwAQCkzcFDLKAlhHw82HYSCh4HcEroZFXRcF9L1dVwX8tcp4MgColxtShCEBtFjhSLJ/9XCQJBSFp2RAiimEoWoPRJliQIsgzs2wNp49fAlm8Rj0QSokIsAZo2S4ieimYQyiqA0nIIkRIgUgKIkWR7QqMIUjLjxaOQ48m/sSgQi0KORhOJEmKxxN+4lHCjE0SIB3VAWbfjIDbVng+hpEsPNCx7HUJFOeSGBgiRCITyCiAehxyPA6IAoaQUKCkFysoSf5W4rFg0YR0SxMR36gGdIDSKoEwXD63rRBFOjSdDOWk5z5kmmedeq131OqOuXnZaiDIFnB/IdZyskG9CWi/aK1Qo57KEqutQ3JCQccstt+Dnn3/G+eefj1tuuQVHHHFEzlh7s1gWO3V1dXj55ZcxdepUfPzxx5BlGa1atcJVV12F6667LpXhTEEURVxzzTVYuHAhlixZUnDHjdKxY0f06tULq1evxiuvvILbbrstbf2KFStQU1OD8vJyDBgwwLV+FQ16lqCwDMBz4BvB41Mcn1/H5jgdOxBEEXI8DiH5uxBLIkkRJKe5ogmikBBAyf81+5wcwMuyAEEWAElVbu8uyPt2J+wz6gGUnEwkIMlAPJb4HI8n9jvemP4asgw5pv4+KYiS30OWIMXigCRj34KXVBnlBAiRCCIVFSg9/GgITZs1iiWgUeQo/QEgow6IRCCWlScETySSsPjEYok+KqgHeJFIowhS/tdCTu6zcq3JclI4ydkiSQsD7omp60wQtMvkEjzqAXZO0a6xLtc+G9m2W5g9JkZxIm29GXcyNUbFR74+00oYepigQJv33nsP3bp1w4wZM2yfTBsoQOx06NAhZW76xS9+gZEjR+Liiy9GkyZNctZr27YtGhoarG7WErfeeit+97vf4aGHHsJZZ52VsuBs37495Rt4/fXXo6rKvcn8ip7MAVxIxY/yRt7zhAU+O762CR2n4nQ06+pYdfL0QRBEQJQSrgtSHIIgQBZFCFDqiclxX6NlRxAFCCURiJEIhJJI+u9FlhJl5aSFRxAT2dCgSlogyIk6gpgQL+q6yQlPU8In33EQxLS2E+IsYZ2SIUFABIKQrK+INAGI13wFRJJWJCnRH1mS0h/bykNNliHV1wEN9RBKSyGUlEKORTV/P4IgJgVO0tojaYgd9cNSvZ/J4506Z2r3OqVMPNNyk3He9SwwyvdaD2q9wX2mxSkfskqkabWpJywA50SP1XubH4RYJrkEjxfxYH5F77dA8kKxo40kSTjuuOMcETpAAWJn586dOOecczBy5Ej079/fcL2bb74Zl1xyidXNWmLQoEEYOXIkJk+ejN69e6N///6orKzE0qVLsXPnTvTp0wf33nuvq30iGYRc/Hhu5fGR4LFtIlEn43RyWXUy3V2SnwVVggEgacWBlLadhJUmUV4WEyJH0AkuVoSOIIgpa4/mfirWHUklSkQAymelnqQWN1JK+KTtt46wFEQhIdbi6aJHEBPJFRSXcsWykzh0MgRBhixK6W54WiiDTFlOWIKi0cTxU0Sb2vomSkAsaQUTxGQWyUiGm5uYXi/NhUpHCOZCfVzicW1Bk0/05Pr9m7FcalmSMhOGqNtTi6PUdyYGqU7et8wKHrtd4bSwEuzvtrhx0pUt896m9b0b/QgpFDva9OzZE5s2bXKsfcti5+uvv8Zhhx1mut6RRx6JI4880upmLTNp0iT06dMHU6dOxcqVKxGNRnH44Ydj/PjxGDNmDMrKylzvE8mBeoAWEjwVPHYfR7f2w6uEBApWss4JIgRRShc+KutOwqLTKJhk1WBBeauliBshmQ5eS+gkrDqJtKSCICZEhVrwIDkQUY/nUy5TcdVkp0nBlBU/IKTXTfZPsUrJUqLfgjrUSExYWwRBu8+pfhsYICXKqXZHGdxKjVakhJsdgHi8UVAp4kepJ6sET0JdArLYKHqsoJxaLYuSGwPfpDBMbVNL6KgEZKpcqozNfcz8zZl5O5tP8Oi6D7ogfBTCbKnJFx9kpD4Fj2EodrS5+eabcc455+Cdd95Bv379bG/fstixInS85g9/+AP+8Ic/eN0NYgb1YCQEwscTweMjoWOL+5rNCQmMkmm5AZKDf1nWDW7OtO4oFhIBUsoqkvkYSwkGUUhZdTIzkslywn0s+SFppckQPIJGnzJcuvLOAZQUUSnhIIoQFKsUNOomhY52etwCxAWQPSjOaC+1L3FAUNaphFGqDUVopqxfMHdNq/sgZh5f2Dvw1hMNRq9pvbf0TqP329Xbn0LviZn1jZwDL5M4WOlvJrlcycIszgIOU09r84tf/ALjxo3DgAEDMGrUKJx11lno3LkzRJ37VufOnU21H+LJYkjo8JErVmAIm9Cxu04S0yJUV9w0CqIstzb1NpTJOTMFg/J9UuhkWXUyb/ypSUal9LgfSU4OxHViOhT3NaPXR4a1SrHwZBVze/I7HQGlWHwEtTVIS/BoCbb0hrIH6OrdlrQexPHCRB2gyhZn4PxkxifprbOSxlivTq4yuUSVWRGUr64d4smC5daWdvTqmhU+fhA2Rqw7Rq4lo/VoSQodXbp0Sb08fPjhh/Hwww/rlvV8nh1CHCfggsdVq05QhU4u3HqwF3qdqdzf1NYdxZ1NQT3fglrUNAodMWtdCiVWRpIaA+0lVYxMSvBk1EHGdah2YcuXbEGJ3Um60GWR2d80oWZeAGS5vGm5POWwGMmylC54UhgUJIKYLXjUb9T1fhOZIsjIYDYrCYUBlP7pkU8s5Yo9ykWhrk9A+oDV6ouKQtznrOL0PdxN9zw7sXpvtlLPjMD2GXRj06Zz586Oviyj2CHBI6CCp1iFjvltuXBuzVxDacLFnCtbWvnkNtUZxjJFjDruJJWUIPldzgeBkpkt6ZolJ0WOoGF5kFXWHd2g9kxEITGAT/Y516R4qX1K9VvMWO/AwMSKi5zW+c9sQxFXWoPqnIO0HOsyd19TjGnV08nyZhbBBpGR1p7FAYrRN/ZmUj7bfe9w21KZSb7za1QMFXL/DoLgSqWW94GVKw8UO9p89913jrZPsUOICwRa6BQJWa5sFkV1SuBkWnckKS3xhmaGMjE9QUHCfUwnBgYqy4faupOM30kF8GthYr/SjougEjyZok89GFeyoVlBy3UsbX2egPas5hqPQf6scBqiSfMYmhgAZu5LZqyFkXuDYqkzg97xN7o9o1gRGIXGIumVt1tIO/3ipVAx5cZzJdc2giCEfAbFToJYLIaSEvckCMUOCSYBse4EPhkBUPADNXAubEYxOOO6IgwUi0aa6NEsr5NmurGA9vcp647YKHgA/SQfyfOa8/xkBvmrRJxuHwsROhoYzd5WcAIEdTsKdggGPfGmkb5cE7W7nJnBpZF7QSH7l4t8/SwkdicXdt8jnHaPMhOH5EfMJFqwIylDCJBhIUFBCMXOQQcdhIEDB2Lw4ME444wzUF5e7uj2KHYIcYhQCB3AWvplqzjwJjVlVXGDzDl3NCwh+QbuajewXFYdPdIEj55FwIjQUfdJse6oBY+qHaW/ANIG0ELGd7a5sOlO0plb8KTF8BihEAGl7mO+wb2RGJhcMUJG0DtemdghGK26X1n9/TslEAq9b1i53s0mpfAThSSG0Lomck0JEFCkRC5O03XCRosWLfDiiy/ib3/7GyorKzFgwAAMHjwYAwYMQGVlpe3bo9ghxAE8nUCUuE4qbkdzZbolJNP9q7FYRqxLmmhoTEetiSw3ZkQShHTBo0Oa0DEwwMoSPKq+ptASOvoN5t2mE1gSPApmhUDeOWSMxo0JyHJ/S/XPYOyLUeuQEy9NDLkGwvog1q8CwYhYckoQmcVrAVVoBr0AC6Bi5LvvvsOHH36I119/HXPmzMGsWbPw2muvoby8HGeccQYGDx6Mc889Fy1btrRlexQ7RuEPiRiAIsefaFp3Co3J0SPTupOolPiby/1LXU7dVh6yM5bJ6YJHp04+0uKMMvc3z6A/TUzYYCnQ3BeL1h3AguAx0Xb2xjT6aTbjlnpiUCvZ0jIz2mnh5DPO6PVjJgudWQoVCG5aj7zILuaUa6FbyBITFASME044ASeccAIefPBBfPbZZ3j99dcxe/ZszJs3D/Pnz0dJSQmqq6vx+9//HoMGDcKBBx5oeVscwZtBEAt7IBRanySQZF/G63gudGyMk/Al+QYATj6UddMFq1JHa2w/S9go9wC9JVkny6qjR+bvIJWVqHH+Ha0lDWWQY0QAGbh/6ZVJEytOD6AM3B8s/16t3HuUgZjWgMzMIE2W8y+afTbQfmYf7Vyy+lPgPdzqdgvByLE3ci6MIEn2LW7uN8mLMqmo2SXs/OIXv8Cdd96J//73v/jqq6/wwAMP4Nhjj8WiRYswYsQIHHzwwfjNb36DKVOmYNOmTabb58jbCkYFi8ZARvN7iiDj+FDkEBtxaBDsWsyOgloEZU4MmgPdCUSNvOnNFC1GBh9GBygZ7mm6giaHW5spNPqleQ5zDWj9JnjyYdfgvBDB4xT5RI/Rxep27RRqprbvAzFgt/jJBYVRXmQ0WneML8VF165dMW7cOLz//vvYsGEDHn30UZx88sn417/+hZEjR6Jz5844+eSTsWTJEsNtcoRtlbz+6GZSdwbD/OoZhTzsio2wW3f8iJ51J0OgKKIn15Kqp0zOqWovl2DKEgJqwaMeWOgNOAzFFmTPCZS55CrvGIVmCyxE8Ph1Piu9QaWdFgMrg+hCn3WFih8rGBVCRvbND4N/py1BRilSAUTLjjk6deqE0aNH491338XmzZvx5JNPorq6Gh9++CFWrlxpuB3G7HgNRU42ARU1WfO0kNCSN25HQRE8FmaVTwkdM/776jTHSsIC5XsLZMU6GY1zyhRG+fbB4D4aTkOtYDDGxnIMj4ltGMZKmumc7cnOuw0C6ddbPjL30Wr2NqeeFUbPp1a/zcZjper5JKaoEMFTaKyR37LxOQBjdqxz0EEHYcSIERgxYgR+/vlnbN++3XBdip1C0EvJ68asxmEkoCKHhBjDg/vGeVI0M7PlEj0aAwRLQkchU/Dka0cvhkePfMck30DRiYFJrqxnQRQ8gL2ix4+CBzD+DLQqIKxiV0puI+mV7SLf79at86/GrUQLyr4XiXWIAK1atUKrVq0Ml6fY8QKKnEYocOwnIBOuBg4T8w3ppqLON8eOzoAkMy01oBqcJwfaOa0eBbyt1c1kBxjKsmWXVUdBdz/DKHiA3Ptlqh2V4FFnd7MbIwK7EIyIQCdEhtF7aq5rwKoFyw4y70deiB8jeJGJzkWsuKUVgxvb5ZdfbqhcWVkZ2rRpgxNPPBEDBgxAWVmZoXoUO3Zj5gZczIR0MB5aV7YCJhZ1dVLPAjFz/rJc2VTWnURbyXl1DM1ho/EwK+Sh79ab/HwpqN0euFDw5GlHzv7sxwk5DSXkMNG+kbJ2CQ2TadrTKOTZYbb/fnUZ88o65BIyALNnOZyjpXSmT58OQP+5mfm9IAho27Yt/vrXv+L000/P2z7FTqHoDQLDOOAlhJgmZ+poLTQSGxglzeph49t72wSrTQMl07E7ChQ8Gu06aOWxitPWIS2ccjmzyyUuH4W41JvajsvucmbuOwF4qUbLjjYvvPACPvzwQ0yZMgUdOnTA//zP/6BLly4QBAHfffcdZs+ejZqaGlx33XVo27Ytli1bhnfeeQeDBg3Chx9+iO7du+dsn2KnEChyrBNiVytfWHdCfHx1ccNfO+PlhqZ1B7D+0M0ldJSBi+lJLVX9yzcQsfEYum7VUcgnCih4dNp2yRpohrTkGB5YCQFnjrcd92Yj15fecyhs7nIBggkKtDnppJNw3XXXYfTo0Zg4cSJKS0vT1k+cOBHjx4/HM888g/fffx+333477rrrLtxzzz147LHH8Oyzz+ZsP1z2QSdxesIyEiosD5JI4NC0vKjSR+dFKVuARccwBaR4NSNeChY6BgZIOS1NNt2fC3pp4dTLBiefP34O8PYiPTJgLO20FxSSftvNeYesTMbq5+uwQJh6Wps777wT7du3x6OPPpoldACgtLQUjzzyCNq3b48777wTAHDbbbehffv2WLZsWd72OSIj3hHyOWFyTb5IAkQh16layOgtGmQJHRPXkSF3M63BhJHYIlHMK2R01xt9w2viTbBlwWNikOhLwQM4K3j8Ptj0QvRk4uVkpWrcnoPOLcFXJOKHJFi+fDl69eqV0+1bEAT06tUL7777LoCEADrmmGOwefPmvO3TjY2QsFKMrmxuoBGnZ3jenbxNuxjToo7VMDmYsM1FzcvgYxOuZr50aQOKz60tEy9ie+zC7hgb5f6jlylRwYk5obSw+7o0co8KgCiiG5s2u3btws8//5y33M6dO7F79+7U51atWhmKiw3gHYKEipBbdwC6tJki18PK6ze5eRBEwbJYyVlXff2oyth2XQVggJCLgtzZ3LTwOOnW5hRBeavuB0uPHdhhMcl3rSnrzSxW8Nri5VOsHP5ieGd5+OGH45133sE333yjW+brr7/GP//5Txx++OGp77Zs2YIDDjggb/schRHiAsUseIKSdjonJtzKjIoepVzOskavG42noSxJ/jn2XloI/CJ4TG7LFE4PFIMgeIBwCB7Af4N+N0fcIRc/imXH7BJ2hg0bhvr6evTr1w/Tpk3Dvn37Uuv279+P559/HtXV1WhoaMDQoUMBANFoFB9//DH+3//7f3nbpxsb8Z4icbfyRZY2khfD5ynP3EMFu6RlCp1c7eVYZzlNc4DIu482ZWgDCnRpM7kt0xS7WxsQbNc2NU5mg7NKpqucGziVEtwjmHpam9GjR+Odd97BggULMHz4cAwfPhxt2rSBIAj46aefAACyLGPAgAEYPXo0AODzzz/Hcccdh4suuihv+8G+akh4KAJ3NqC4LTx58bsLm9Y16sT5FETb2/XUwhOEATIQDgsPQAuPAl3bnMOqL5Ydflk53eD8f30yOZ02kUgE8+bNw+OPP45DDz0Usizjp59+wo8//ghZlnHIIYfgsccew7x58xCJRAAAxx57LP75z3/iwgsvzNs+LTvEP+QLrCTFiyj6Y+CiZYVUCxOnZkDPEFqhEM1ezJuS77jRwmOgbVViiyAQNkuPEYJwf/DCSkR8jSAIGDlyJEaOHIlNmzZh48aNAIAOHTqgY8eOBbVNsUP8h/rmR+HjH/K4bQUSHRfKnK5sudwulUGGUTc4o320AU/c2VwcEBvLQGevCChawQMEx61NISyixwh+dIHTI21S5hwvPEMiiiQIkEzG4JgtHwY6dOiADh06aK7bvn27oaQEagLwSyBFjSiE5iYXeCwIHVfdp9wceOW7JhVXtFyLxe0ExqrjwUDY2BxD9iUssAWnXdro1pZOWNzbjOBHF7hc5HJxC0l6Mk4qqs3YsWMNlautrcUZZ5xhuv2APDVJ0UPBQ1wmr6hwUogHXeT7/Y2/nzK0mdyeJZieOhuKnmATUNHDmB1t/vKXv+Cpp57KWWbfvn0YMGAA/u///s90+xQ7JDgEfQAYZML2oDSIISuKcl0Wem0aaKdQq45vUlEHAQoek+0HdERWjKInTKmdAyZ6mHpamyOPPBIjR47EggULNNc3NDTgvPPOw7///W+cd955ptun2CHBg6InEARmYJ3nWjIlMNSCRe861SpjZF6eYnFfK3DQbPi6MzLQo+Ax2X5wBp1ZFJPoURMW8RMQ0cNJRbVZuHAhWrVqhQsuuABr1qxJWxePx/GHP/wBS5cuxemnn46ZM2eabj8gT09CNKDoIQbJG7huQPBYFhsmRY2l9v2CUaHjlyBxCh4H2g+4300xCh41YRA+JHAcdthhmDdvHiRJwjnnnIOamhoAibl1LrnkEsybNw99+/bF3LlzUVpaarp9nzxxCCkAPw32/IRdgya/JyawCx9bVwJh1fFRnI6p68+vgifIiQuA4AueIN7D7Iaix36sJCcoggQFANC7d2+8+OKL2Lp1KwYMGIDa2loMHz4cM2bMwPHHH48FCxagSZMmltpm6mkSDnKlAyYECetO3kGwgetIER62DGrzEAiREwb8lpJawcnU1IA76akBXwlhUxRTuupcqO91vCcVhBXDZ5DfG5hl8ODBmDhxIm6++WZ0794dP/zwA4466igsWrQIzZs3t9wur1pCSNFgaJ4Zg4PLglzbDLafE7px5sR266LJlym2ieGgu7UBwR+t0dLTCN3cCkKZZ8fsUkzceOONuOaaa/DDDz/gsMMOw9KlS03Pq5MJLTskPNC6Yz8WH2iGrChZlQT/DIpMXEtqUWLXANeQ0PETPn1zb2oiVSNWDpOWFlp41NsI2CSkWtDSk07m/Y5Wn7zQspPg8ssvz7k+Ho+jtLQUXbp0wa233pq2ThAETJs2zdT2Qi92Fi5ciPfffx8ffvghPvzwQ2zZsgUAUFNTg44dO3rcO1JsuOH6RHJjWIhZEM96A1uj591wqusg4+eBYrELHoBubUag6NGG7m7EINOnTzdUbtmyZVnfUexoMGTIENTW1nrdDeIWtO4QAzgpeDS3Z9eDP+hCxwheD4SLWfAAtPKYQX0PofBJh8JHk1TSAZN1CuG1117D1KlT8fHHH6OhoQFdu3bFRRddhDFjxljKbAYAb7zxBqZNm4b3338fO3bsQMuWLdG1a1eceeaZuOOOO/LWf+GFFyxt1yqhFzu///3vccQRR+D444/H8ccfj4MOOsjrLhHiPHYIviBaoUy4wrkteArGhkGuYZcukh8KngK3ERIrj4IkUfDoQeGTwkqixUIeP6NHj8akSZNQUlKC6upqNGvWDMuWLcO4ceMwf/58vP3226YynDU0NODiiy/Ga6+9hiZNmuDkk09G27ZtsXXrVnz22WeYPHmyIbFz2WWXWd8pC4Re7Dz//PNed4EQ4iZOCR7AO9FTDBYdBT+89Tc62KfgsWE7PjjfdkH3tvwUeZyPmzE7c+fOxaRJk9CsWTMsX74cxx9/PABg27ZtqK6uxooVKzBhwgQ88sgjhtu86qqr8Nprr2HQoEH43//9X7Rp0ya1TpIkvP/++9Y66zDFdZWR4qCYBoZO4UerjkMDCFPWDrczoIUt41qQBoEO/QYCk6UNcC/rVtAnIs1Eyd7GDG75KbLsbjIES4sVHnjgAQDA+PHjU0IHANq0aYMnn3wSADBlyhTDoR5Lly7Fiy++iB49emDWrFlpQgcARFFE7969DfdtwYIFhsrqsWDBgtQ+5iNATx5CiCH84HIFj12mTL4pNt1XN0RImEROmLHwewuU4AHcG4iGSfAoUPQYRy18Qip+JDS6shleLGxn06ZNWL16NYBE7Homffv2RadOnVBfX4+FCxcaavOJJ54AkHCNsxrro3D77bdj9uzZBbXx+uuvY8KECYbKht6NjRBSpJhMZW0pXbZakNg18HRI5DBexwIOubMBNru0AeFyawPC49qmQBc38zDWxzJr1qwBALRu3RqHHnqoZpkTTzwRNTU1WLNmDS688MKc7cXjcSxduhQA8Ktf/Qpbt27FjBkzsHbtWpSXl6Nnz54YPHgwmjVrZu+O2ATFjkF2769L+1xeWoLyUh4+4jN8YtVxDFE095bUDcGjUKjwCaolx8eDUlsEXhAEj8Xtm8aN9NSpbYUolkcNRY81QiJ83IrZWb9+PQCgc+fOumU6deqUVjYX3377Lfbs2QMA+M9//oNrr7029VnhpptuwowZM1BdXW2oj6+//jreeecdQ2W12LZtm+Gyvh2t33zzzZg3b57pes899xz69u1re3+6Xvdg2ufbBp+G288/3fbtEEJsxk3Bo2AmoYELIodWnQKh4EmHyQsKh6LHOgFOclCI2Nm1a1fa9+Xl5SgvL9ess3v3bgBAZWWlbruKFSazXS22b9+e+v+KK67AKaecgkceeQTdu3fHunXrcOutt2LhwoU477zz8NFHH+GII47I2+aePXuyBJNZBIP3B9+Knc2bN2Pt2rWm6xV64PT4ZuotaN6kIvWZVh0fE3brRrFj1roDeCN4gNyiJ6iWnAAhS1IghB4FT67thNStTYGip3AU8ROAOB9JFiCZnDdHKa9YYhTuvPNO3HXXXXZ1LSey6vnZoUMHLFq0KCW0jj32WMybNw/HHXccPv30Uzz00EN5J/00Yk2yE9+O2F966SW89NJLXncjRfMmFWjRtCJ/QUK8wk6RJ4jePDiMipIgCR4gW/S4KHR8M9j3Sz+s4qB1Bwiw4AFo5bEDTlBaFBRi2ampqUGLFi1S3+tZdQCgefPmAIC9e/fqllGMA+o287UHAEOHDs3adiQSwdVXX40//elPWLJkSd72DjnkkLxl7MS3YocQEnxsFQyZBE3wALTmeICt1h0KHm1o5bEXWntCSyFip0WLFoaECQB06dIFQEIg6aGsU8rma08QBMiyjMMOO0yzjPL9li1bDPXRTfhLMoogNi6EWMC2dLNu4dW1bmYgY2UwYCEttW+sIyQ4WLS02nqfcNOl1837W9jm5dGDaauJRXr27AkgEWuj5zL2wQcfAEDaHDx6NGvWDN26dQOgnxhA+d6PGdn4BLeCWvgYXQhxkrDFKflM8ACNosdt4VPI9ijSEthqnTMzqPfD79JtweO26CkGKHpCg2x2jh2Lur5jx47o1asXAOCVV17JWr9ixQrU1NSgvLwcAwYMMNTm+eefDwC6bmqLFy8GAJx00knmO+wwoX8S3nvvvejdu3dqURg4cGDqu2uvvdb5jlAEkSDi5TXqtOApADdEhFpYUbT4DIcH9LZbgZVRk1vQyuMMFD2BR5YFS4sVbr31VgDAQw89hI8++ij1/fbt21Pj3uuvvx5VVVWpdXPmzEH37t3Rv3//rPZGjhyJVq1aYeHChXjmmWfS1s2YMQMvv/xyqpzfCH3Mzrp167Bq1aqs75UJlwCgosLDxANag8mguTsRb/HD22OnMBNj4/AcPFnVbYznMSJmHI1/KgJsz8wWpPidAvtiCbfieFLbC3kCAzWM6Qksbs2zAwCDBg3CyJEjMXnyZPTu3Rv9+/dHZWUlli5dip07d6JPnz6499570+rU1tZi7dq1qKury2qvTZs2mDlzJgYOHIgRI0bgiSeewFFHHYV169alxtQTJkwwbClyk9D/UqZPnw5ZlnMuhUxq5Ai0/hDSiJMWngIHR3a4tZmp71RZXxHGAasf4ncUwu7WVixWHqDR0sOXIIHBrAtboUbZSZMmYebMmTj55JOxcuVKLFy4EB07dsRDDz2EZcuWoUmTJqbaO/300/Hxxx/jsssuw86dO/HGG2/g+++/x4ABA7Bo0SLcc8891jvrIIIsF9OdwTy7du1CVVUVfnjhXv+knqblJzc+tHQ4mpzAjf0toP+2WSOM3qqsbM+G26DZ/SxEjOTblqtCx6g4MdonB8WOI8fFzAspi1YV2y08gPuZAd1+cRdG0WyEoL7ksIFd++rQ9tJbUVtbazhrmVsoY8mp82vRpNJc3/bv3YXrzq3y5X4FheL9VQQZWnxIMWL3oNpK27maMGHlcdMaRBrx3A2wWC08AK08bkFLDyFZhD5mJ9QogoeWnuJGFHxpzVKwNdbE6UlHgYIHSIoQ0dpnO0WK3nYohFzGpdgUx2J4AHetPIzlcQfG9fgSN2N2SCMUO2GAoof4HE8Ej8ftq/fZSQFCceMDzAzgC0gS4IjgAdxNXAA0PqvcEj3FMhmpFhQ9vsJKDI6P32UGBl79YYLubb7ElclE3fa/t4Ctc9QYGbQUsi2bBkWckNQCDr/G9NyVDSho9OLY/cSLEZXbL+iK+RU5kxn4AsWyY3YhhUHLThgRRFp5ihGfu7MpuJpC2Yo7m4LTFiQSLlx0zwqNhQfwxq0NKE4rjwKtPZ5hRW9SnxYOr/SwUswWngBYOQKHzdeTLdYONwYrglDcgyJiDjMvmQp8MRE6C48XVp5if5lBS4/r0LLjDUU8Ii4Cilnw+ARXXNjUBEjouebeFRRhRYoPPwueYnBrAziSBCh6SOjhaDjsMI6H+JiCY1qcTEdtdVvE9zjqRml2wO5XwQPQylNsUPQ4Di073sCYnWKh2OJ4AhK/4ghO7buD15CrcTyFwDge4kMci+EBvInjAdyP5QEYz6PAmB7HkGAhG5sjPSkuKHaKiWITPKQ4cHLuHSfINZCikAoHZgfqXgkKo3gpeACKHq+g6LEdWZYhm7zPmy1PsuEVTIhDuB6vo8bPAycdXInhEcXCH9yFDIDy1S32wVWYCJM7G+BdHA/g3Us6DjITMG21bdCNzRto2Sk2ism6U8yubE7h8PVj2Z3NrHtZoVYetSgxst2wipgA75csSaGbA8lRdzYFWnmKG1p7CkK2oBmLZcjmJLxaixEmLCCFEJbrx84JTvUGQlZSV3NQFR5ctu4ALlmUvXyJ5EUCA4Cv2DOhpYcEiJCMWgghWTj59tXBLH+W37ZbEQl2vp1UhI16Ib7Gl0kxKHiMQdc2f0DRYwq6sXkD3diKlWJyZyPOoQgev1xLVrKl+SVxgZowZn2TpOJ0fbGSVcwGVzHXXNoA72IE6drmH+jeZggroW9ev1cIA7wqi5mwuCMR77H5WnI9lsKPD2gOpEiBuJYkxevRmJdWnrC9lCgUWnpyQsuON9CyU+zQwuMYgiB6m5HNbfxi5bFqFfGjhYc4jiuJCjyy7gAuWXgA79Nne2XlARL3G76cSEd9L/XjyySPkCUZssmXA2bLk2wodggJM15kpPODgA6LG1hY9oNQ8LgFXdv8B13cUtCNzRt45ZFwu7N5/eAtVoJ6TfnxYczBk+P4MlFBUPFyPh41dG3zH3RxIx7hwyc78YSgDk59jitvU/1KgftesGsRRQLxG1YG4DYJB9ddav0ieCh6/EcRix7G7HgD3dgIcZiii91R47VLG7OzEYP4epLRoLmzKXidrU3B63gegC9ftChC9zZJkiGZfBFgtjzJpniuMJKfYrZCOIynFh6vBxpe4/X8O4So8fjFhycvXvwyWPPy2PMVvT5FZOmhZccb+EQn6VDwOAYFj3lse9MeBsHjtzfDfuuPDfg6dsdGwVD0gsdr0UO0KQLRQ7HjDXRjI9l47XoUYjx1afMiMxvgn+vJbZc2RSzZ+fCmO5vj+DYVNWBrtjPXXdoA/7i1AXRt8zMhdm+TZBmSyXu42fIkm/BdSYT4HFp4zGHrwNNpC48oNi5W6gcFDtJCgWcvXvxi5QG8t/JwIKuPYukJubWHOA8tO0Qbv7yNLxQ/PVRVeG7hAXx7bBzHbguP22KG1p1w4APrDuCRhQfwx5w8Cl5aeQBaeowQEmuPFS/KMAzFvIZih+gTFsHjUzzP0lbMoseq4LGKHzO8EV18nZktTPjJrQ2g6AkCARc9MmTIJp89MorwGW0zFDskN8pNn6InvARA9Aii6O/gcSPYKXiCat2RpMAOUhyh2K07Cn6y8gAUPUEgoKJHtuCVx+FX4VDsEGPQyhN+vEpg4BVBFQwKQe9/LmSZA718UPA4j1Uxatv2+TvIS8BEjyxbsOyE9T7vIhQ7xDgUPLbjuStbJk5ZeWy4dhS3IlstPG4LBrqzBQbXXNm8HlCr8IXgAfwlemjlCQYBSWQgyeYfr8X0DtIp/HGHDQK80STwyUOZOIyfBhsZMJZChRf3Jd4L/YMDoyBfvHzx4+jOD/Pz8A0/IZagZccMykO+2G84tPAUBz6O5bE1hifo1p0wu7MVCz6y7gA+sPAA/rTyALT0kIKQJRmyyWeq2fIkG4odK6hvMsU6yKDgIR4TiqQFQaIIB1eByMrmUKyLLwQP4M9YHoCih1jCioGuWIeZduKDO5lz/Pjjj3jxxRcxZMgQHHHEEaioqEDTpk3RvXt3jBw5Et99913hGxEE3mwI8QjbBqJu/4btHkA73X/e45ynkJdHYX/zayXQwS28fulH97ZAIUmypYUURqjFzg033IDLLrsMM2fORNOmTTFw4ED85je/wY4dO/DEE0+gR48eWLx4sT0bK0bR44e3fvnw4xvBDHzx9pQU3+/XKEV+XIrZeuiL+B01fh30eR3PA1D0BAQlG5vZhRRGqN3YWrdujbvvvhtXXHEFOnTokPp+z549uOqqqzBjxgxccMEF+Oabb9CqVSt7NlpscT10ZyMe47o7m19/44zdCT6FxO6E3Z1Nwa9ubYD3rm0A3dt8jhVdzCFW4fjoDmY/kydPxh133JEmdACgWbNmmDZtGpo3b44dO3ZgwYIF9m+8mCw9Gjf2+mgM9722GPXRmAcdysCvD0YVbg4m6qMx3Dd7ifFzY9fxc3AfbXVny7eoyxaCRp/rozHc/8Y7/vjdAN7ew3wk3BQxXR+N4b6/L/PP+XEJX1p4Mqw8vnrm0NKTRn00hvtmLfLHuSFFSajFTi6aNm2Kbt26AQBqamqc21CxCJ4M6qMx3G9mQE1coz4awwNFOGBzBJt/3/WxOB6Y9y7qY3Fb2yX2UB+L4YG5/0R9zMHfjk9jd3wneIC0/fXlM4eiB0Dy3LzuEyHqMZIsW1pIYYTajS0X0Wg0laCgffv2zm7Mr24vduJ3dzZR8K+/dxLfTTAaMJidDfa6sjn1okaSAjPbuZqiv7b8is/v6wDo3kZSWInBYcxO4RSt2Jk2bRq2bduGJk2a4KyzznJno8UgegjJhcOi2BPBU4jAsHvOHRIOfBi7A/gwfkcNRY/BPlD0eImV7GrMxlY4RSl2PvnkE9x0000AgAkTJqBt27a6ZRVFvXlHLXbvr0t9X1ZSgvLSAg9f2ESPahCrHCv1MfMFAblpOGnh2b2/Pu2vIey8Vh22Xnn2Bt7qMVJdk5bOjV39yMTJwZDRwbjPBmS2nB+jFDogdvDY+VHwpJ45e/d73BOD+OUYuvAbc2s8oLTvZ0sI59nxBkH26VVx8803Y968eabrPffcc+jbt6/u+o0bN6Jv377YsGEDBg4ciLlz50LI8WPfuHEjOnXqZLofhBBCCCHEXWpqatCxY0evu5HGrl27UFVVhasf2ojyiham6tbX7cIz4zuitrYWLVqYq0sS+Nays3nzZqxdu9Z0vT179uiu27p1K/r3748NGzbgt7/9LWbNmpVT6ADAwQcfjHXr1qG0tDStbHl5OcrLy033jxBCCCGE2Issy9i9ezcOPvhgr7tCfIZvxc5LL72El156ybb2fvzxR1RXV+Orr77Caaedhrlz5xoSK6Io4rDDDrOtH4QQQgghxH6qqqq87kJOZAvZ1XzqgBUofCt27OSnn35CdXU1vvjiC/Tv3x/z5s1DRUWF190ihBBCCCFFgizJkE3GDpstT7IJvdjZtm0bqqur8dlnn6F///6YP38+mjRp4nW3CCGEEEJIEUGx4w0+SQfiDDt27ED//v3x6aef4rTTTqPQ8Rl79uzBYYcdBkEQIAgCNm7c6HWXipIff/wRL774IoYMGYIjjjgCFRUVaNq0Kbp3746RI0em5qMizvLaa6+hX79+aNWqFSorK3Hsscfi4YcfRjQa9bprRUk0GsXSpUtx0003oVevXmjZsiVKS0vRrl07DBw4EAsWLPC6iySDm2++OfU8ue+++7zuDgHQ0NCAyZMno2/fvmjdujUqKirQsWNHnHXWWZg5c6bX3XMdSba2kMIItWXnyiuvxH//+18IgoDWrVvjmmuu0Sw3aNAgDBo0yN3OEdx0000cSPuAG264AS+//DJEUUSPHj0wcOBA7N27F6tXr8YTTzyB559/HnPmzMHpp5/udVdDy+jRozFp0iSUlJSguroazZo1w7JlyzBu3DjMnz8fb7/9Nl/UuMzy5ctT13y7du3Qt29fVFZW4vPPP8f8+fMxf/58DB8+HE8//XTeRDfEeVauXIlHH30UgiAwxsEnbNy4Eb/97W/x+eefo02bNujTpw8qKytRU1ODd999F5WVlfjjH//odTddhZYdbwi12NmxYweARHDXrFmzdMt16dKFYsdlFi9ejKeffhrXX389pkyZ4nV3iprWrVvj7rvvxhVXXIEOHTqkvt+zZw+uuuoqzJgxAxdccAG++eYbtGrVysOehpO5c+di0qRJaNasGZYvX47jjz8eQKML7ooVKzBhwgQ88sgjHve0uBBFEYMHD8aoUaNw6qmnpq2bOXMmLrroIjz77LPo06cPLr30Uo96SQBg3759GDp0KNq3b49evXph7ty5Xnep6Nm/fz9OP/10fPnll7jrrrtw6623orS0NLV+3759+OqrrzzsISkmfDvPDgkvu3btQo8ePVBSUoJPPvkEzZo1A+DP3PjFzr59+9CuXTvs3r0bf/vb33DxxRd73aXQcdJJJ2H16tW47777cNttt6WtW7FiBU499VSUl5fjhx9+8H2moWLiyiuvxLRp09C/f38sWbLE6+4UNaNGjcLkyZOxYMECzJo1C3/9619x77334vbbb/e6a0XLHXfcgXvvvRfDhw/HM88843V3PEeZZ2fonetRZnKenYa6XZh+96GcZ6cAQh2zQ/zJ6NGjsXHjRjz33HOorKz0ujskB02bNkW3bt0AJMQosZdNmzZh9erVAIAhQ4Zkre/bty86deqE+vp6LFy40O3ukRz07NkTAH8XXvPOO+/giSeewKWXXooBAwZ43R2CRLzbU089BSDhrk4akSRAkmSTi9e9Dj6hdmMj/mPBggV44YUXMHz4cFRXV3vdHZKHaDSaiqtq3769t50JIWvWrAGQcCU89NBDNcuceOKJqKmpwZo1a3DhhRe62T2Sg6+//hoAfxdesmfPHlx++eVo27YtHn/8ca+7Q5J89NFH2LZtGw4++GB07doVn3zyCf7+979j8+bNaNWqFU499VScddZZEMXie98uy7LpmDI6YBUOxQ5xjZ9//hlXXXUVOnXqhD//+c9ed4cYYNq0adi2bRuaNGmCs846y+vuhI7169cDADp37qxbplOnTmllifds3boV06dPBwAMHjzY284UMTfeeCPWr1+POXPmMJ7QR/z3v/8FAHTs2BHjx4/Hww8/nDZgnzhxInr27Im5c+fmvPeFESYo8Ibik9XEM66//nps2bIFzz77LP1OA8Ann3ySckGYMGEC2rZt63GPwsfu3bsBIKc7pxLTtmvXLlf6RHITi8Vw8cUXo7a2Fscccwyuvvpqr7tUlLz99tt45plncMEFFzDBkM/Yvn07gITleuLEibj22muxdu1a1NbWYvHixTjyyCOxZs0anH322UWXWl8RO2YXUhi07JC83HzzzZg3b57pes899xz69u0LAPj73/+OV155BcOGDcOZZ55pdxeLFjvOjRYbN27Eueeeiz179mDgwIEYP358Id0kJDSMGDECS5cuxQEHHIDXX38dZWVlXnep6KitrcUVV1yBAw88EE888YTX3SEZKFacaDSKCy+8MC3j6mmnnYbFixejW7du+PTTTzFjxgxccsklXnWVFAkUOyQvmzdvxtq1a03X27NnD4BECt1rrrkGBx98MB577DG7u1fUFHputNi6dSv69++PDRs24Le//S1mzZrFeUQconnz5gCAvXv36pZRzhWtod4zatQoTJs2Da1atUq9oSbuoyS5mTlzJtq0aeN1d0gGyn0NgKbls3Pnzjj77LMxe/ZsLFmypKjEjgQZkskYHAm07BQKxQ7Jy0svvYSXXnrJcv0VK1bgxx9/RMeOHXO6G5x//vkoLy/H0KFDMXToUMvbKyYKPTeZ/Pjjj6iursZXX32F0047DXPnzkV5eblt7ZN0unTpAiB3Ri9lnVKWeMPYsWMxefJktGzZEm+//XYqGxtxnzlz5qCkpARPPvkknnzyybR1X375JYBEvOGSJUvQrl07zJgxw4tuFi2HHXaY5v9aZbZs2eJKn/wCY3a8gWKHuMbGjRuxceNG3fX/+c9/AAD9+vVzqUdEzU8//YTq6mp88cUX6N+/P+bNm4eKigqvuxVqlAHz9u3bsX79es2MbB988AEApCYbJe5z880347HHHkNVVRXefvttnHjiiV53qeiJxWJYvny57vrvvvsO3333HQ455BAXe0WAxL1KEATIsoxt27alkqyo2bZtG4DGmMRigdnYvIEJCojjDBo0KPUD11oUampqIMsy7rrrLu86W6Rs27YN1dXV+Oyzz9C/f3/Mnz8fTZo08bpboadjx47o1asXAOCVV17JWr9ixQrU1NSgvLycc4h4xPjx4/HnP/8ZVVVVWLx4cep8Ee/YuXOn7vPksssuAwDce++9kGU5lTqfuEe7du1SMaFaE+5Go9GUUD3ppJNc7ZvXyKbn2GGCAjug2CGkyNmxYwf69++PTz/9FKeddhqFjsvceuutAICHHnoIH330Uer77du349prrwWQyGRYVVXlSf+Kmdtvvx0TJ05Ey5YtKXQIMcGdd94JAHjwwQdTXhtAwiI3duxYfPvtt2jevDmGDRvmVRdJEUE3NkKKnCuvvBL//e9/IQgCWrdujWuuuUaz3KBBg5ji1QEGDRqEkSNHYvLkyejduzf69++PyspKLF26FDt37kSfPn1w7733et3NomPevHm4//77AQBdu3bF1KlTNcu1adMGjzzyiJtdI8T39O/fH/feey8mTJiAU089FSeddBLatWuHjz76CN999x2aNGmCV199teimNGDMjjdQ7BBS5OzYsQNAwi941qxZuuW6dOlCseMQkyZNQp8+fTB16lSsXLkS0WgUhx9+OMaPH48xY8YwvbEHKL8LIBE3pcROZXLIIYdQ7BCiwe23346TTjoJjz/+OFatWoXVq1ejXbt2GDp0KMaNG4fu3bt73UXX8SJm57XXXsPUqVPx8ccfo6GhAV27dsVFF12EMWPGoLS0tKC2Fy5ciLPPPhtAQuBquS36AUFm5BMhhBBCCCGOsGvXLlRVVWHwyE9RWt48fwUV0frdmD25B2pra01PQTB69GhMmjQJJSUlqK6uRrNmzbBs2TLs3LkTffv2xdtvv23Zbf3nn39Gjx49sGXLFsiy7Guxw5gdQgghhBBCHMZscgJlscLcuXMxadIkNGvWDKtWrcKiRYswe/ZsfP311zjmmGOwYsUKTJgwwfK+/OlPf8IPP/yAESNGWG7DLSh2CCGEEEIIcZhcmWmNZK01wwMPPAAgkVFSPXVBmzZtUvNTTZkyBbW1tabbnjNnDl5++WXccMMNgcioR7FDCCGEEEJISNi0aRNWr14NABgyZEjW+r59+6JTp06or6/HwoULTbW9bds2jBgxAt26dcM999xjS3+dhmKHEEIIIYQQh1GysZldzLJmzRoAQOvWrTUnqwaQmhxZKWuUa665Btu2bcO0adMCM/E4s7ERQgghhBDiMG6lnl6/fj0AoHPnzrplOnXqlFbWCDNmzMDrr7+OUaNGoU+fPqb75RUUO4QQQgghhDiMBAmSLJmuAyQyuqkpLy9HeXm5Zp3du3cDACorK3XbbdasmWa7emzduhXXXXcdDj/88FQ8UFCgGxshhBBCCCEOI0tWXNkSdTt16oSqqqrU8uCDD7ra9+HDh+Pnn3/Gc889h6ZNm7q67UKhZYcQQgghhBCHKcSNraamJm2eHT2rDgA0b56Yy2fv3r26Zfbs2QMAhubu+etf/4r58+fjmmuuQb9+/Yx021dQ7BBCCCGEEOJjWrRoYXhS0S5dugBICCQ9lHVK2VzMmTMHALB69eossbN161YAwIcffphaN2PGDLRr185QX92AYocQQgghhBCHsTJvjpV5dnr27AkA2L59O9avX6+Zke2DDz4AgLQ5ePKh1NFi586dWL58OQCgrq7OTHcdhzE7hBBCCCGEOIwkSZYWs3Ts2BG9evUCALzyyitZ61esWIGamhqUl5djwIABedubO3eu7oSnL7zwAgCgf//+qe+MWIvchGKHEEIIIYQQh3Frnh0AuPXWWwEADz30ED766KPU99u3b8e1114LALj++utRVVWVWjdnzhx0794d/fv3L2Av/Qfd2AghhBBCCHEYWZYgm0w9bba8wqBBgzBy5EhMnjwZvXv3Rv/+/VFZWYmlS5di586d6NOnD+699960OrW1tVi7dq3v3NAKhZYdQggJOX/6058gCAJOPfVUxGKxrPW33XYbBEHA8ccfH7qHHCGE+AU3LTsAMGnSJMycORMnn3wyVq5ciYULF6Jjx4546KGHsGzZMjRp0sTGvfMvgmwl8okQQkhgaGhoQJ8+ffDBBx9g3LhxeOihh1Lr3nrrLQwYMADNmzfHhx9+iK5du3rYU0IICR+7du1CVVUVTrtoJUrLmpmqG23YgyUvn4La2lrD2dhIOrTsEEJIyCkrK8OsWbPQsmVLPPzww3jzzTcBABs3bsQll1wCWZbx3HPPUegQQoiTWLHqFGDZIQkodgghpAg49NBDMX36dMiyjEsuuQTr16/HBRdcgG3btuH666/H+eef73UXCSEk1EiyZGkhhUGxQwghRcJ5552HG264Adu3b0fPnj3x3nvv4cQTT8Sjjz7qddcIIST0uB2zQxJQ7BBCSBExceJEHH300aitrUVlZSVmzZqFsrIyr7tFCCGhR5YlyJLJhZadgqHYIYSQImLVqlX46quvAAB79+7FJ5984nGPCCGkOKBlxxsodgghpEjYtm0bLrjgAsRiMQwbNgyCIGDo0KHYsGGD110jhBBCHIFihxBCigAlMcHGjRtx6aWX4vnnn8fYsWPx888/449//COi0ajXXSSEkFCjTCpqdiGFQbFDCCFFwIMPPoi33noLRx99NJ588snUdyeffDJWrVqFm2++2eMeEkJIuJEkQJJkk4vXvQ4+FDuEEBJy3n33Xdxxxx1o2rQpXnvtNVRWVgIASkpKMGPGDLRu3RqPP/443njjDY97Sggh4cV0coLkQgqDYocQQkLMTz/9hAsvvBDxeBxTp07F0Ucfnba+c+fOmD59OgRBwLBhw/Ddd99501FCCAk5TFDgDSVed4AQQohzHHjggdi0aVPOMueeey4kvj0khBBHsRKDw5idwqFlhxBCCCGEEBJKaNkhhBBCCCHEYay4pdGNrXAodgghhBBCCHGYWMNu0wkH4rG9DvWmeKDYIYQQQgghxCHKysrQrl07fLD0D5bqt2vXDmVlZTb3qngQZFmmfYwQQgghhBCHqKurQ0NDg6W6ZWVlqKiosLlHxQPFDiGEEEIIISSUMBsbIYQQQgghJJRQ7BBCCCGEEEJCCcUOIYQQQgghJJRQ7BBCCCGEEEJCCcUOIYQQQgghJJRQ7BBCCCGEEEJCCcUOIYQQQgghJJT8f8MjkGxNRM2rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.compile(optimizer=\"L-BFGS\", loss_weights = weights)\n",
    "model.restore(save_path=\"./Model/model-75000.pdparams\")\n",
    "plot_flow_field()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4b1c579c-3ba9-4745-93e3-502d173c1bb4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-01T03:23:52.203885Z",
     "iopub.status.busy": "2023-11-01T03:23:52.203275Z",
     "iopub.status.idle": "2023-11-01T03:23:52.209745Z",
     "shell.execute_reply": "2023-11-01T03:23:52.209036Z",
     "shell.execute_reply.started": "2023-11-01T03:23:52.203847Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0021739"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum([4.88e-04, 4.71e-04, 2.49e-04, 2.48e-04]) + np.sum([3.73e-03, 8.16e-04, 1.68e-03, 9.53e-04])/10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71e5f75c-3cf8-4ed4-9ce7-6c154f2e2027",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def plot_ref_flow_field():\n",
    "    import matplotlib as mpl\n",
    "    from matplotlib import rcParams\n",
    "    config = {\"font.size\": 16}\n",
    "    rcParams.update(config)\n",
    "    plt.rcParams['xtick.direction'] = 'in'\n",
    "    plt.rcParams['ytick.direction'] = 'in'\n",
    "    '''------------------------------------------- Model validation ---------------------------------------------'''\n",
    "    '''------------------Plotting 2------------------'''\n",
    "    data_points = np.load('../1_Fluent_results/level' + str(level) + '_fluent_results.npy')\n",
    "    data_xy = data_points[:, 0:2]\n",
    "    u = data_points[:, 2]\n",
    "    v = data_points[:, 3]\n",
    "    p = data_points[:, 4]\n",
    "    rho = data_points[:, 5]\n",
    "\n",
    "    airfoil_plot = airfoil_boundary_points[:, 0:2]\n",
    "\n",
    "    # plot\n",
    "    fig, ax = plt.subplots(figsize=(10, 4), dpi=300)\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], (u**2 + v**2)**0.5, levels=1000, cmap=\"coolwarm\", vmin=36.5, vmax=467)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=36.5, vmax=467)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[m/s]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Velocity Magnitude')\n",
    "    plt.show()\n",
    "    # plt.savefig(\"./Figs/Velocity.png\", dpi=500)\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(10, 4), dpi=300)\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], p, levels=1000, cmap=\"coolwarm\", vmin=19900, vmax=100000)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=19900, vmax=100000)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[Pa]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Pressure')\n",
    "    plt.show()\n",
    "    # plt.savefig(\"./Figs/P.png\", dpi=500)\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(10, 4), dpi=300)\n",
    "    ax.tricontourf(data_xy[:, 0], data_xy[:, 1], rho, levels=1000, cmap=\"coolwarm\", vmin=0.341, vmax=1.13)\n",
    "    plt.axis('scaled')\n",
    "    plt.fill(airfoil_plot[:, 0], airfoil_plot[:, 1], color = 'w')\n",
    "    norm =mpl.colors.Normalize(vmin=0.341, vmax=1.13)\n",
    "    plt.rcParams['ytick.direction'] = 'out'\n",
    "    plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=\"coolwarm\"), ax=ax, label='[kg/m^3]')\n",
    "    plt.rcParams['ytick.direction'] = 'in'    \n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title('Density')\n",
    "    plt.show()\n",
    "    # plt.savefig(\"./Figs/Rho.png\", dpi=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a7165c3-f260-4e79-99e4-af8d6489fb44",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "plot_ref_flow_field()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "420b113a-5753-4107-9b49-c2efb8933536",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "py35-paddle1.2.0"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
